Kyivstar.Tech

Kyivstar Tech is looking for a Network Security Engineer.

What will you do

• Operate, administer, and evolve the company’s network security infrastructure
• Automate routine firewall operations and policy management using Python and APIs
• Investigate network and security incidents; perform traffic analysis and root cause identification
• Collaborate with IT, DevOps, and Security teams to implement secure network designs
• Document configurations, topologies, and workflows for internal and audit use

Qualifications and experience needed

• Experience with Cisco ASA and Cisco Firepower Threat Defense (FTD) firewalls
• Managing and configuring security policies using Cisco Firepower Management Center (FMC)
• Experience administering and configuring Fortinet (FortiGate) security solutions
• Strong knowledge of VPN technologies (IPSec, SSL VPN), NAT, ACLs, routing, and IPS/IDS on Cisco and Fortinet platforms
• Deep understanding of network protocols and services: TCP/IP, UDP, DNS, DHCP, VLANs, STP, ARP, OSPF, BGP
• Excellent troubleshooting skills for network connectivity and security incident investigation
• Experience with traffic monitoring, packet capture (e.g., tcpdump, Wireshark), and log management tools
• Experience with cloud technologies, Azure, AWS
• Ability to maintain accurate technical documentation, including network diagrams and configuration records
• English proficiency is sufficient for technical documentation and communication with vendors/support

• Proficiency in Python for automation of security operations: 

  - scripting policy deployments, configuration validation, auditing, and integrations 

  - working with REST APIs, JSON/XML, and CLI tools 

A plus would be

• Exposure to Palo Alto, Check Point, or other NGFW platforms
• Knowledge of Zero Trust architecture, NAC, and microsegmentation
• Experience with log aggregation and SIEM tools (e.g., ELK, Splunk)

What we offer

• Office or remote – it’s up to you. You can work from anywhere, and we will arrange your workplace 
• Remote onboarding  
• Performance bonuses for everyone (annual or quarterly — depends on the role)  
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners   
• Health and life insurance  
• Wellbeing program and corporate psychologist  
• Reimbursement of expenses for Kyivstar mobile communication 

Kyivstar.Tech is looking for VAS planning and development engineer

What you will do:

• Prepare and follow up system strategy: 

- HW and SW lifecycle

- Dimensioning

- Load prediction

- Budgeting and budget execution

• Partner and contract management: 

- Contract scope and terms definition and control (supply, service, NDA)

- Contract technical part preparation (solution description, scope of work, scope of supply)

• Initiate and participate in tender: 

- Technical requirements definition (architecture, features, services, etc.)

- Offers analysis, clarification with participants

- Technical evaluation

• Lead system deployment, system extension, new services (HW/SW/services): 

- Initiate purchase orders

- Coordinate HW supply with partner and logistic function

- Control SW supply, including needed documents preparation 

- Coordinate works with partner, O&M team, other supporting functions: prepare plan, schedule, supervise execution, control 

• Collect business needs and prepare technical requirements for new services/solutions 

• Provide consultancy to business about systems functionality

• Support complex works execution at maintenance window 

Qualifications and experience needed:

• GSM/UMTS/LTE architecture knowledge 

• PS domain elements knowledge: 

- PCRF/PCEF/TDF, DRA, OCS, DPI, GGSN/PGW

- Corresponding 3GPP interfaces

- Signaling protocols: GTP, Diameter 

• IP network knowledge

• English level: Pre-intermediate or higher

• Preferred: 5G architecture knowledge, SQL knowledge, Linux based OSs 

 Target system: 

• PCRF and TDF 

Opportunity: 

• 5G NSA and 5G SA deployment. 

• Participate in large-scale modernization projects. 

• Get wide experience of how business works. 

• Get deep PCRF knowledge. 

• Bring optimization to the existing PCRF system. 

What we offer:

• Office or remote — it's up to you: you can work from anywhere, and we will arrange your workplace

• Remote onboarding

• Performance bonuses for everyone (annual or quarterly — depends on the role)

• We train employees: the opportunity to learn through the company’s own library, internal resources and programs from partners

• Health and life insurance

• Wellbeing program and corporate psychologist

• Reimbursement of expenses for Kyivstar mobile communication

We are looking for a Data Engineer to build and optimize the data pipelines that fuel our Ukrainian LLM and Kyivstar’s NLP initiatives. In this role, you will design robust ETL/ELT processes to collect, process, and manage large-scale text and metadata, enabling our data scientists and ML engineers to develop cutting-edge language models. You will work at the intersection of data engineering and machine learning, ensuring that our datasets and infrastructure are reliable, scalable, and tailored to the needs of training and evaluating NLP models in a Ukrainian language context. This is a unique opportunity to shape the data foundation of a pioneering AI project in Ukraine, working alongside NLP experts and leveraging modern big data technologies.

What you will do

• Design, develop, and maintain ETL/ELT pipelines for gathering, transforming, and storing large volumes of text data and related information. Ensure pipelines are efficient and can handle data from diverse sources (e.g., web crawls, public datasets, internal databases) while maintaining data integrity.
• Implement web scraping and data collection services to automate the ingestion of text and linguistic data from the web and other external sources. This includes writing crawlers or using APIs to continuously collect data relevant to our language modeling efforts.
• Implementation of NLP/LLM-specific data processing: cleaning and normalization of text, like filtering of toxic content, de-duplication, de-noising, detection, and deletion of personal data.
• Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
• Set up and manage cloud-based data infrastructure for the project. Configure and maintain data storage solutions (data lakes, warehouses) and processing frameworks (e.g., distributed compute on AWS/GCP/Azure) that can scale with growing data needs.
• Automate data processing workflows and ensure their scalability and reliability. Use workflow orchestration tools like Apache Airflow to schedule and monitor data pipelines, enabling continuous and repeatable model training and evaluation cycles.
• Maintain and optimize analytical databases and data access layers for both ad-hoc analysis and model training needs. Work with relational databases (e.g., PostgreSQL) and other storage systems to ensure fast query performance and well-structured data schemas.
• Collaborate with Data Scientists and NLP Engineers to build data features and datasets for machine learning models. Provide data subsets, aggregations, or preprocessing as needed for tasks such as language model training, embedding generation, and evaluation.
• Implement data quality checks, monitoring, and alerting. Develop scripts or use tools to validate data completeness and correctness (e.g., ensuring no critical data gaps or anomalies in the text corpora), and promptly address any pipeline failures or data issues. Implement data version control.
• Manage data security, access, and compliance. Control permissions to datasets and ensure adherence to data privacy policies and security standards, especially when dealing with user data or proprietary text sources.

Qualifications and experience needed

• Education & Experience: 3+ years of experience as a Data Engineer or in a similar role, building data-intensive pipelines or platforms. A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred. Experience supporting machine learning or analytics teams with data pipelines is a strong advantage.
• NLP Domain Experience: Prior experience handling linguistic data or supporting NLP projects (e.g., text normalization, handling different encodings, tokenization strategies). Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given our project’s focus. Understanding of FineWeb2 or a similar processing pipeline approach.
• Data Pipeline Expertise: Hands-on experience designing ETL/ELT processes, including extracting data from various sources, using transformation tools, and loading into storage systems. Proficiency with orchestration frameworks like Apache Airflow for scheduling workflows. Familiarity with building pipelines for unstructured data (text, logs) as well as structured data.
• Programming & Scripting: Strong programming skills in Python for data manipulation and pipeline development. Experience with NLP packages (spaCy, NLTK, langdetect, fasttext, etc.). Experience with SQL for querying and transforming data in relational databases. Knowledge of Bash or other scripting for automation tasks. Writing clean, maintainable code and using version control (Git) for collaborative development.
• Databases & Storage: Experience working with relational databases (e.g., PostgreSQL, MySQL), including schema design and query optimization. Familiarity with NoSQL or document stores (e.g., MongoDB) and big data technologies (HDFS, Hive, Spark) for large-scale data is a plus. Understanding of or experience with vector databases (e.g., Pinecone, FAISS) is beneficial, as our NLP applications may require embedding storage and fast similarity search.
• Cloud Infrastructure: Practical experience with cloud platforms (AWS, GCP, or Azure) for data storage and processing. Ability to set up services such as S3/Cloud Storage, data warehouses (e.g., BigQuery, Redshift), and use cloud-based ETL tools or serverless functions. Understanding of infrastructure-as-code (Terraform, CloudFormation) to manage resources is a plus.
• Data Quality & Monitoring: Knowledge of data quality assurance practices. Experience implementing monitoring for data pipelines (logs, alerts) and using CI/CD tools to automate pipeline deployment and testing. An analytical mindset to troubleshoot data discrepancies and optimize performance bottlenecks.
• Collaboration & Domain Knowledge: Ability to work closely with data scientists and understand the requirements of machine learning projects. Basic understanding of NLP concepts and the data needs for training language models, so you can anticipate and accommodate the specific forms of text data and preprocessing they require. Good communication skills to document data workflows and to coordinate with team members across different functions.

A plus would be

• Advanced Tools & Frameworks: Experience with distributed data processing frameworks (such as Apache Spark or Databricks) for large-scale data transformation, and with message streaming systems (Kafka, Pub/Sub) for real-time data pipelines. Familiarity with data serialization formats (JSON, Parquet) and handling of large text corpora.
• Web Scraping Expertise: Deep experience in web scraping, using tools like Scrapy, Selenium, or Beautiful Soup, and handling anti-scraping challenges (rotating proxies, rate limiting). Ability to parse and clean raw text data from HTML, PDFs, or scanned documents.
• CI/CD & DevOps: Knowledge of setting up CI/CD pipelines for data engineering (using GitHub Actions, Jenkins, or GitLab CI) to test and deploy changes to data workflows. Experience with containerization (Docker) to package data jobs and with Kubernetes for scaling them is a plus.
• Big Data & Analytics: Experience with analytics platforms and BI tools (e.g., Tableau, Looker) used to examine the data prepared by the pipelines. Understanding of how to create and manage data warehouses or data marts for analytical consumption.
• Problem-Solving: Demonstrated ability to work independently in solving complex data engineering problems, optimising existing pipelines, and implementing new ones under time constraints. A proactive attitude to explore new data tools or techniques that could improve our workflows.

What we offer

• Office or remote – it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.   
• Health and life insurance.  
• Wellbeing program and corporate psychologist.  
• Reimbursement of expenses for Kyivstar mobile communication.  

Kyivstar.Tech is seeking an experienced Senior Data Scientist / NLP Lead to spearhead the development of cutting-edge natural language processing solutions for our Ukrainian LLM project. You will lead our NLP team in designing, implementing, and deploying large-scale language models and NLP algorithms that power our products. This role is critical to our mission of advancing AI in the Ukrainian language context, and offers the opportunity to drive technical decisions, mentor a team of data scientists, and shape the future of AI capabilities in Ukraine.

About us

Kyivstar.Tech is a Ukrainian hybrid IT company and a resident of Diia.City.

We are a subsidiary of Kyivstar, one of Ukraine's largest telecom operators.

Our mission is to change lives in Ukraine and around the world by creating technological solutions and products that unleash the potential of businesses and meet users' needs.

Over 500+ KS.Tech specialists work daily in various areas: mobile and web solutions, as well as design, development, support, and technical maintenance of high-performance systems and services.

We believe in innovations that truly bring quality changes and constantly challenge conventional approaches and solutions. Each of us is an adherent of entrepreneurial culture, which allows us never to stop, to evolve, and to create something new.

What you will do 

• Lead end-to-end development of NLP and LLM models - from data exploration and model prototyping to validation and production deployment. This includes designing novel model architectures or fine-tuning state-of-the-art transformer models (e.g. BERT, GPT) to solve project-specific language tasks.

• Analyze large text datasets (Ukrainian and multilingual corpora) to extract insights and build robust training datasets. Guide data collection and annotation efforts to ensure high-quality data for model training.

• Develop and implement NLP algorithms for a range of tasks such as text classification, named entity recognition, semantic search, and conversational AI. Stay up-to-date with the latest research to apply transformer-based models, embeddings, and other modern NLP techniques in our solutions.

• Establish evaluation metrics and validation frameworks for model performance, including accuracy, factuality, and bias. Design A/B tests and statistical experiments to compare model variants and validate improvements.

• Deploy and integrate NLP models into production systems in collaboration with engineers - ensuring models are scalable, efficient, and well-monitored in a real-world setting. Optimize model inference and troubleshoot issues such as model drift or data pipeline bottlenecks.

• Provide technical leadership and mentorship to the NLP/ML team. Review code and research, uphold best practices in ML (version control, reproducibility, documentation), and foster a culture of continuous learning and innovation.

• Collaborate cross-functionally with product managers, software engineers, and MLOps engineers to align NLP solutions with product goals and infrastructure capabilities. Communicate complex data science concepts to stakeholders and incorporate their feedback into the model development process.

Qualifications and experience needed 

Education & Experience:

• 5+ years of experience in data science or machine learning, with a strong focus on NLP.

• Proven track record of developing and deploying NLP or ML models at scale in production environments.

• Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Deep understanding of natural language processing techniques and algorithms.

• Hands-on experience with modern NLP approaches, including embedding models, text classification, sequence tagging (NER), and transformers/LLMs.

• Deep understanding of transformer architectures and knowledge of LLM training and fine-tuning techniques, hands-on experience developing solutions on LLM, and knowledge of linguistic nuances in Ukrainian or other languages.

Advanced NLP/ML Techniques:

•Experience with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.

•Background in information retrieval or RAG (Retrieval-Augmented Generation) is a plus for building systems that augment LLMs with external knowledge.

ML & Programming Skills:

•Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn).

•Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.

•Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.

• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.

• Experience in building a representative benchmarking framework given business requirements for LLM.

• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.

• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).

• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop) for scaling data processing or model training is a plus.

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).

Leadership & Communication:

• Demonstrated ability to lead technical projects and mentor junior team members.

• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.

A plus would be 

LLM training & evaluation experience:

• Experience with tokenizer development, SFT, and RLHF techniques.

• Knowledge of model safety: toxicity, hallucinations, ethical considerations, and LLM guardrails.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.

• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicating a passion for staying at the forefront of the field.

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and cultural context for model training and evaluation.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).

• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Creative mindset for tackling open-ended AI challenges.

• Comfort in fast-paced R&D environments with evolving priorities.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.

• Remote onboarding.

• Performance bonuses.

• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.

• Health and life insurance.

• Wellbeing program and corporate psychologist.

• Reimbursement of expenses for Kyivstar mobile communication.

We are seeking an experienced Senior/Middle Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and personally train LLMs with a strong focus on Reinforcement Learning from Human Feedback (RLHF). You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards. The benchmarks and feedback loops you own serve as the contract for quality—gating releases, catching regressions before users do, and enabling compliant, trustworthy features to ship with confidence.

What you will do

• Analyze benchmarking datasets, define gaps, and design, implement, and maintain a comprehensive benchmarking framework for the Ukrainian language.
• Research and integrate state-of-the-art evaluation metrics for factual accuracy, reasoning, language fluency, safety, and alignment.
• Design and maintain testing frameworks to detect hallucinations, biases, and other failure modes in LLM outputs.
• Develop pipelines for synthetic data generation and adversarial example creation to challenge the model’s robustness.
• Collaborate with human annotators, linguists, and domain experts to define evaluation tasks and collect high-quality feedback.
• Develop tools and processes for continuous evaluation during model pre-training, fine-tuning, and deployment.
• Research and develop best practices and novel techniques in LLM training pipelines.
• Analyze benchmarking results to identify model strengths, weaknesses, and improvement opportunities.
• Work closely with other data scientists to align training and evaluation pipelines.
• Document methodologies and share insights with internal teams.

Qualifications and experience needed

Education & Experience:

• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
• Proven experience in machine learning model evaluation and/or NLP benchmarking.
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Good knowledge of natural language processing techniques and algorithms.
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
• Familiarity with LLM training and fine-tuning techniques.

ML & Programming Skills:

• Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
• Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
• Solid understanding of RLHF concepts and related techniques (preference modeling, reward modeling, reinforcement learning).
• Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.
• Experience creating and managing test datasets, including annotation and labeling processes.
• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.

Communication:

• Experience working in a collaborative, cross-functional environment.
• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.

A plus would be

Advanced NLP/ML Techniques:

• Prior work on LLM safety, fairness, and bias mitigation.
• Familiarity with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
• Knowledge of data annotation workflows and human feedback collection methods.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and context.
• Understanding of cultural and linguistic nuances that could inform model training and evaluation in a Ukrainian context.
• Knowledge of Ukrainian benchmarks, or familiarity with other evaluation datasets and leaderboards for large models, can be an advantage given our project’s focus.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Innovative mindset with the ability to approach open-ended AI problems creatively.
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation.

What we offer:

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses for everyone (annual or quarterly — depends on the role).
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners. 
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.

We are seeking an experienced Senior/Middle Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will focus on designing and prototyping data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines and actively develop model training pipelines with other talented data scientists. Your work will directly shape the quality and capabilities of our models by ensuring we feed them the highest-quality, most relevant data possible. The datasets you build directly determine model capability, safety, and cost, raising downstream task accuracy, reducing training waste, and accelerating time-to-market for product teams.

What you will do

• Design, prototype, and validate data preparation and transformation steps for LLM training datasets, including cleaning and normalization of text, filtering of toxic content, de-duplication, de-noising, detection and deletion of personal data, etc.
• Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
• Analyze large-scale raw text, code, and multimodal data sources for quality, coverage, and relevance.
• Develop heuristics, filtering rules, and cleaning techniques to maximize training data effectiveness.
• Collaborate with data engineers to hand over prototypes for automation and scaling.
• Research and develop best practices and novel techniques in LLM training pipelines.
• Monitor and evaluate data quality impact on model performance through experiments and benchmarks.
• Research and implement best practices in large-scale dataset creation for AI/ML models.
• Document methodologies and share insights with internal teams.

Qualifications and experience needed

Education & Experience:

• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
• Proven experience in data preprocessing, cleaning, and feature engineering for large-scale datasets of unstructured data (text, code, documents, etc.).
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Good knowledge of natural language processing techniques and algorithms.
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
• Familiarity with LLM training and fine-tuning techniques, and data requirements.

ML & Programming Skills:

• Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
• Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
• Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.
• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.

Communication & Personality:

• Experience working in a collaborative, cross-functional environment.
• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.
• Ability to rapidly prototype and iterate on ideas

A plus would be

Advanced NLP/ML Techniques:

• Familiarity with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
• Understanding of FineWeb2 or a similar processing pipeline approach

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations)

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and context.
• Understanding of cultural and linguistic nuances that could inform model training and evaluation in a Ukrainian context.
• Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given our project’s focus.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Innovative mindset with the ability to approach open-ended AI problems creatively.
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.

We are hiring an MLOps Engineer specializing in Large Language Model (LLM) infrastructure to design and maintain the robust platform on which our AI models are developed, deployed, and monitored. As an MLOps Engineer, you will build the backbone of our machine learning operations — from scalable training pipelines to reliable deployment systems — ensuring that our NLP models (including LLMs) can be trained on large datasets and served to end-users efficiently. This role sits at the intersection of software engineering, DevOps, and machine learning, and is crucial for accelerating our R&D in the Ukrainian LLM project. You’ll work closely with data scientists and software engineers to implement best-in-class infrastructure and workflows for the continuous delivery of AI innovations.

What you will do

• Design and implement modern, scalable ML infrastructure (cloud-native or on-premises) to support both experimentation and production deployment of NLP/LLM models. This includes setting up systems for distributed model training (leveraging GPUs or TPUs across multiple nodes) and high-throughput model serving (APIs, microservices).
• Develop end-to-end pipelines for model training, validation, and deployment. Automate the ML workflow from data ingestion and feature processing to model training and evaluation, using technologies like Docker and CI/CD pipelines to ensure reproducibility and reliability.
• Collaborate with Data Scientists and ML Engineers to design MLOps solutions that meet model performance and latency requirements. Architect deployment patterns (batch, real-time, streaming inference) are appropriate for various use-cases (e.g., a real-time chatbot vs. offline analysis).
• Implement and uphold best practices in MLOps, including automated testing of ML code, continuous integration/continuous deployment for model updates, and rigorous version control for code, data, and model artifacts. Ensure every model and dataset is properly versioned and reproducible.
• Set up monitoring and alerting for deployed models and data pipelines. Use tools to track model performance (latency, throughput) and accuracy drift in production. Implement logging and observability frameworks to quickly detect anomalies or degradations in model outputs.
• Manage and optimize our Kubernetes-based deployment environments. Containerize ML services and use orchestration (Kubernetes, Docker Swarm or similar) to scale model serving infrastructure. Handle cluster provisioning, health, and upgrades, possibly using Helm charts for managing LLM services.
• Maintain infrastructure-as-code (e.g., Terraform, Ansible) for provisioning cloud resources and ML infrastructure, enabling reproducible and auditable changes to the environment. Ensure our infrastructure is scalable, cost-effective, and secure.
• Perform code reviews and guide other engineers (both MLOps and ML developers) on building efficient and maintainable pipelines. Troubleshoot issues across the ML lifecycle, from data processing bottlenecks to model deployment failures, and continuously improve system robustness.

Qualifications and experience needed

Experience & Background:

• 4+ years of experience in DevOps, MLOps, or ML Infrastructure roles
• Strong foundation in software engineering and DevOps principles as they apply to machine learning
• A bachelor’s or Master’s in Computer Science, Engineering, or a related field is preferred

Cloud & Infrastructure:

• Extensive experience with cloud platforms (AWS, GCP, or Azure) and designing cloud-native applications for ML
• Comfortable using cloud services for compute (EC2, GCP Compute, Azure VMs), storage (S3, Cloud Storage), container registry, and serverless components where appropriate
• Experience managing infrastructure with Infrastructure-as-Code tools like Terraform or CloudFormation

Containerization & Orchestration:

• Proficiency in container technologies (Docker) and orchestration with Kubernetes
• Ability to deploy, scale, and manage complex applications on Kubernetes clusters; experience with tools like Helm for Kubernetes package management
• Knowledge of container security and networking basics in distributed systems

CI/CD & Automation:

• Strong experience implementing CI/CD pipelines for ML projects
• Familiar with tools like Jenkins, GitLab CI, or GitHub Actions for automating testing and deployment of ML code and models
• Experience with specialized ML CI/CD (e.g., TensorFlow Extended TFX, MLflow for model deployment) and GitOps workflows (Argo CD) is a plus

Programming & Scripting:

• Strong coding skills in Python, with experience in writing pipelines or automation scripts related to ML tasks
• Familiarity with shell scripting and one or more general-purpose languages (Go, Java, or C++) for infrastructure tooling
• Ability to debug and optimize code for performance (both in data pipelines and in model inference code)

ML Pipeline Knowledge:

• Solid understanding of the machine learning lifecycle and tools
• Experience building or maintaining ML pipelines, possibly using frameworks like Kubeflow, Airflow, or custom solutions
• Knowledge of model serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton, or custom Flask/FastAPI servers for ML)

Monitoring & Reliability:

• Experience setting up monitoring for applications and models (using Prometheus, Grafana, CloudWatch, or similar) and implementing alerting for anomalies
• Understanding of model performance metrics and how to track them in production (e.g., accuracy on a validation stream, response latency)
• Familiarity with concepts of A/B testing or canary deployments for model updates in production

Security & Compliance:

• Basic understanding of security best practices in ML deployments, including data encryption, access control, and dealing with sensitive data in compliance with regulations
• Experience implementing authentication/authorization for model endpoints and ensuring infrastructure complies with organizational security policies

Team Collaboration:

• Excellent collaboration skills to work with cross-functional teams
• Experience interacting with data scientists to translate model requirements into scalable infrastructure
• Strong documentation habits for outlining system designs, runbooks for operations, and lessons learned

A plus would be

LLM/AI Domain Experience:

• Previous experience deploying or fine-tuning large language models or other large-scale deep learning models in production
• Knowledge of specialized optimizations for LLMs (such as model parallelism, quantization techniques like 8-bit or 4-bit quantization, and use of libraries like DeepSpeed or Hugging Face Accelerate for efficient training) will be highly regarded

Distributed Computing:

• Experience with distributed computing frameworks such as Ray for scaling up model training across multiple nodes
• Familiarity with big data processing (Spark, Hadoop) and streaming data (Kafka, Flink) to support feeding data into ML systems in real time

Data Engineering Tools:

• Some experience with data pipeline and ETL
• Knowledge of tools like Apache Airflow, Kafka, or dbt, and how they integrate into ML pipelines
• Understanding of data warehousing concepts (Snowflake, BigQuery) and how processed data is used for model training

Versioning & Experiment Tracking:

• Experience with ML experiment tracking and model registry tools (e.g., MLflow, Weights & Biases, DVC)
• Ensuring that every model version and experiment is logged and reproducible for auditing and improvement cycles

Vector Databases & Retrieval:

• Familiarity with vector databases (Pinecone, Weaviate, FAISS) and retrieval systems used in conjunction with LLMs for augmented generation is a plus

High-Performance Computing:

• Exposure to HPC environments or on-prem GPU clusters for training large models
• Understanding of how to maximize GPU utilization, manage job scheduling (with tools like Slurm or Kubernetes operators for ML), and profile model performance to remove bottlenecks

Continuous Learning:

• Up-to-date with the latest developments in MLOps and LLMOps (Large Model Ops)
• Active interest in new tools or frameworks in the MLOps ecosystem (e.g., model optimization libraries, new orchestration tools) and a drive to evaluate and introduce them to improve our processes

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication

Kyivstar.Tech team is looking for a new colleague for the role of ETL/RAID developer

What you will do

Development of functionality and ensuring the operation of processes:

• Creation of orders and aggregation processes using ETL/ WEDO RAID  
• Development of processes related to data processing, interaction with systems and support of existing processes 
• Testing processes and logic developed in streams
• Work on writing and correcting Batch file, Java-script, Python-script, work with API, CSV, TXT, XML, JSON

• Administration of test environments + provision of recommendations for process changes

   

Qualifications and experience needed

• At least 4 years of experience with SQL programming and development using ETL/ WEDO RAID tools

• Knowledge of Python, Java or similar programming languages ​​will be an advantage

   

What we offer

• Office or remote — it's up to you: you can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses for everyone (annual or quarterly — depends on the role)
• We train employees: with the opportunity to learn through the company’s library, internal resources, and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication

We are looking for a QA Automation Engineer to join our Product Development Team. You will join the in-house development team, whose primary responsibility is building Kyivstar’s web app for customer support. 

What you will do

• Work in a cross-functional team with a product manager, analysts, developers & designers to deliver digital innovations
• Test management (plan, test scenarios design, execution, follow-up, control)
• Acceptance testing (including manual testing)
• Regression testing
• Tests automation and support of existing test builds

• Testing reporting and documentation

   

Qualifications and experience needed

• 2+ years of relevant working experience
• Great knowledge of automation tools (Selenium) and Java
• JMeter, SOAP UI knowledge
• Excellent knowledge of mobile/web UI manual testing principles
• Experience of composing test strategies and test plans
• Test design techniques knowledge
• Experience in integration testing
• Basic SQL knowledge
• Basic knowledge of web front-end technologies (HTML/CSS/JS)
• RESTful API — understanding of principles and experience in tests automation
• Experience working in an Agile/Scrum team
• Good knowledge of Atlassian stack (Jira, Confluence)
• Excellent analytical skills, critical mindset

• Strong communication, negotiation, problem-solving and troubleshooting skills

   

What we offer

• Office or remote — it's up to you. You can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses for everyone (annual or quarterly — depends on the role)
• We train employees: the opportunity to learn through the company’s own library, internal resources and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication

We are looking for a strong Product Owner to lead one of our key products at Kyivstar – our website www.kyivstar.ua, B2C part. In this role, you will be responsible for all aspects of the product, including P&L, KPIs and OKRs, people management, stakeholder management, roadmap prioritization, R&D, customer development, and more. Your goal will be to ensure the successful implementation of our product strategy.

You will join our experienced product team, which includes product designers, business analysts, developers, QA specialists, product analysts, and more - all the expertise you need to succeed. We seek a team member passionate about building great products, who understands how to navigate ambiguity, and thrives in transforming chaos and complexity into elegant solutions. Our in-house team is committed to consistently delivering value to our clients and will support you every step of the way.

What you will do

• Setting your team’s goals and success metrics for Kyivstar’s mission, driving maximum business impact
• Identifying new product opportunities and revenue drivers. Constant adaptation to our customers' needs and the market is a key
• Developing and creating buy-in of the product strategy for the C-level, your team, and all stakeholders
• Inventing new features and working closely with the Discovery and Engineering teams to deliver them and measure them
• Collaborating with other stakeholders: FP&A, Legal, Tech, Marketing, Customer Support, etc
• Prioritizing the product roadmap and aligning it with the IT roadmap of the company, while managing risks, setting expectations, identifying dependencies, and forecasting future development

• Going deep into business and system analysis to ensure good decisions

   

Qualifications and experience needed

• 3+ years of experience in product management with proven success defined by metrics, experience in managing products through the complete lifecycle, from ideation to market launch
• At least 2 years of experience working with web digital products, content management systems, and marketing.
• 1+ years of people management will be a plus
• Metrics-oriented mindset and strategic thinking; strong skills in stakeholder management 
• Strong leadership skills, ability to create and translate product vision, and drive your team to ensure progress
• Understanding telco business specifics is a must
• Technical proficiency to engage effectively with engineering teams and understand API design principles, understanding of basic system integration principles, and ability to define a good technological architecture of the product
• Good written and verbal communication skills. Excellent negotiation skills
• Willingness to tackle any challenges on the path to successful product development

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.

We are looking for a Data Engineer to build and optimize the data pipelines that fuel our Ukrainian LLM and Kyivstar’s NLP initiatives. In this role, you will design robust ETL/ELT processes to collect, process, and manage large-scale text and metadata, enabling our data scientists and ML engineers to develop cutting-edge language models. You will work at the intersection of data engineering and machine learning, ensuring that our datasets and infrastructure are reliable, scalable, and tailored to the needs of training and evaluating NLP models in a Ukrainian language context. This is a unique opportunity to shape the data foundation of a pioneering AI project in Ukraine, working alongside NLP experts and leveraging modern big data technologies.

What you will do

• Design, develop, and maintain ETL/ELT pipelines for gathering, transforming, and storing large volumes of text data and related information. Ensure pipelines are efficient and can handle data from diverse sources (e.g., web crawls, public datasets, internal databases) while maintaining data integrity.
• Implement web scraping and data collection services to automate the ingestion of text and linguistic data from the web and other external sources. This includes writing crawlers or using APIs to continuously collect data relevant to our language modeling efforts.
• Implementation of NLP/LLM-specific data processing: cleaning and normalization of text, like filtering of toxic content, de-duplication, de-noising, detection, and deletion of personal data.
• Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
• Set up and manage cloud-based data infrastructure for the project. Configure and maintain data storage solutions (data lakes, warehouses) and processing frameworks (e.g., distributed compute on AWS/GCP/Azure) that can scale with growing data needs.
• Automate data processing workflows and ensure their scalability and reliability. Use workflow orchestration tools like Apache Airflow to schedule and monitor data pipelines, enabling continuous and repeatable model training and evaluation cycles.
• Maintain and optimize analytical databases and data access layers for both ad-hoc analysis and model training needs. Work with relational databases (e.g., PostgreSQL) and other storage systems to ensure fast query performance and well-structured data schemas.
• Collaborate with Data Scientists and NLP Engineers to build data features and datasets for machine learning models. Provide data subsets, aggregations, or preprocessing as needed for tasks such as language model training, embedding generation, and evaluation.
• Implement data quality checks, monitoring, and alerting. Develop scripts or use tools to validate data completeness and correctness (e.g., ensuring no critical data gaps or anomalies in the text corpora), and promptly address any pipeline failures or data issues. Implement data version control.
• Manage data security, access, and compliance. Control permissions to datasets and ensure adherence to data privacy policies and security standards, especially when dealing with user data or proprietary text sources.

Qualifications and experience needed

• Education & Experience: 3+ years of experience as a Data Engineer or in a similar role, building data-intensive pipelines or platforms. A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred. Experience supporting machine learning or analytics teams with data pipelines is a strong advantage.
• NLP Domain Experience: Prior experience handling linguistic data or supporting NLP projects (e.g., text normalization, handling different encodings, tokenization strategies). Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given our project’s focus. Understanding of FineWeb2 or a similar processing pipeline approach.
• Data Pipeline Expertise: Hands-on experience designing ETL/ELT processes, including extracting data from various sources, using transformation tools, and loading into storage systems. Proficiency with orchestration frameworks like Apache Airflow for scheduling workflows. Familiarity with building pipelines for unstructured data (text, logs) as well as structured data.
• Programming & Scripting: Strong programming skills in Python for data manipulation and pipeline development. Experience with NLP packages (spaCy, NLTK, langdetect, fasttext, etc.). Experience with SQL for querying and transforming data in relational databases. Knowledge of Bash or other scripting for automation tasks. Writing clean, maintainable code and using version control (Git) for collaborative development.
• Databases & Storage: Experience working with relational databases (e.g., PostgreSQL, MySQL), including schema design and query optimization. Familiarity with NoSQL or document stores (e.g., MongoDB) and big data technologies (HDFS, Hive, Spark) for large-scale data is a plus. Understanding of or experience with vector databases (e.g., Pinecone, FAISS) is beneficial, as our NLP applications may require embedding storage and fast similarity search.
• Cloud Infrastructure: Practical experience with cloud platforms (AWS, GCP, or Azure) for data storage and processing. Ability to set up services such as S3/Cloud Storage, data warehouses (e.g., BigQuery, Redshift), and use cloud-based ETL tools or serverless functions. Understanding of infrastructure-as-code (Terraform, CloudFormation) to manage resources is a plus.
• Data Quality & Monitoring: Knowledge of data quality assurance practices. Experience implementing monitoring for data pipelines (logs, alerts) and using CI/CD tools to automate pipeline deployment and testing. An analytical mindset to troubleshoot data discrepancies and optimize performance bottlenecks.
• Collaboration & Domain Knowledge: Ability to work closely with data scientists and understand the requirements of machine learning projects. Basic understanding of NLP concepts and the data needs for training language models, so you can anticipate and accommodate the specific forms of text data and preprocessing they require. Good communication skills to document data workflows and to coordinate with team members across different functions.

A plus would be

• Advanced Tools & Frameworks: Experience with distributed data processing frameworks (such as Apache Spark or Databricks) for large-scale data transformation, and with message streaming systems (Kafka, Pub/Sub) for real-time data pipelines. Familiarity with data serialization formats (JSON, Parquet) and handling of large text corpora.
• Web Scraping Expertise: Deep experience in web scraping, using tools like Scrapy, Selenium, or Beautiful Soup, and handling anti-scraping challenges (rotating proxies, rate limiting). Ability to parse and clean raw text data from HTML, PDFs, or scanned documents.
• CI/CD & DevOps: Knowledge of setting up CI/CD pipelines for data engineering (using GitHub Actions, Jenkins, or GitLab CI) to test and deploy changes to data workflows. Experience with containerization (Docker) to package data jobs and with Kubernetes for scaling them is a plus.
• Big Data & Analytics: Experience with analytics platforms and BI tools (e.g., Tableau, Looker) used to examine the data prepared by the pipelines. Understanding of how to create and manage data warehouses or data marts for analytical consumption.
• Problem-Solving: Demonstrated ability to work independently in solving complex data engineering problems, optimising existing pipelines, and implementing new ones under time constraints. A proactive attitude to explore new data tools or techniques that could improve our workflows.

What we offer

• Office or remote – it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.   
• Health and life insurance.  
• Wellbeing program and corporate psychologist.  
• Reimbursement of expenses for Kyivstar mobile communication.  

Компанія Київстар.Тех в пошуку Engineering Manager, який керуватиме процесами розробки. Твоє завдання - разом із командами створювати продукти, шукати оптимальні та ефективні способи розв'язання задач і при цьому тримати рівень якості інженерних рішень.

Що ти будеш робити

• Тримати технологічне лідерство у своїх командах
• Узгоджувати та шукати кращі інженерні рішення для продукту
• Виконувати роль People Manager для інженерів своїх команд
• Брати участь у створенні/зміні процесів розробки на рівні усіх продуктів
• Вибудовувати з Product Owner ефективну взаємодію, щоб забезпечити баланс технологічних рішень із запитами бізнесу
• Працювати над розвитком інженерів у командах
• Вибудовувати архітектуру рішень разом із командою і технічними лідами
• Брати участь у технологічних проєктах на рівні компанії

Яка кваліфікація та досвід необхідні

• 2+ роки досвіду роботи на позиціях CTO / VP of Engineering / Head of Engineering / Engineering Manager
• 4+ роки практичного досвіду керування розробкою в команді Tech Lead / Team Lead
• Вміти бути "граючим тренером": писати код, щоб розуміти інженерів
• Розуміти на системному рівні архітектуру мобільних додатків (Front/Back) та вебрішень (Front/Back)

Плюсом стане

• Бажання та вміння виходити за межі шаблонів
• Гарний набір софт-скілів, зокрема вміння доводити свою точку зору різній аудиторії
• Знання Англійської мови на рівні Upper-Intermediate (B2) і вище

Що ми пропонуємо

• Ремоут онбординг
• Перформанс бонуси для всіх (річні чи квартальні — залежить від ролі)
• Навчаємо працівників: є безліч внутрішніх ресурсів і програм від партнерів, власна бібліотека
• Страхування здоров’я і життя для працівників
• Wellbeing-програма та корпоративний психолог
• Компенсація витрат на мобільний зв'язок Київстар

Київстар.Тех відкриває нову вакансію у департаменті систем взаємодії з клієнтами.

Про нас

Kyivstar.Tech — українська гібридна ІТ-компанія, резидент Дія.City. Ми є дочірньою компанією Київстар, одного з найбільших українських операторів зв’язку.

Наша місія — змінювати життя в Україні та у світі, створюючи технологічні рішення і продукти, що реалізують потенціал компаній і потреби користувачів.

Понад 600 спеціалістів KS.Tech щодня працюють у різних сферах: мобільні та веб-рішення, а також проєктування, розробка, підтримка та технічне обслуговування високопродуктивних систем і сервісів.

Ми віримо в інновації, що дійсно приносять якісні зміни, та постійно кидаємо виклик традиційним підходам і рішенням. Кожен з нас є адептом підприємницької культури, яка дозволяє ніколи не зупинятися, розвиватися і створювати нове.

Що ти будеш робити

• Аналізувати бізнес-потреби внутрішнього/зовнішнього замовника, з врахуванням можливих обмежень та розробкою архітектурних рішень
• Експертну оцінку проєктної документації замовника (брифи, концепції, інше)
• Узгоджувати вимоги між внутрішнім/зовнішнім замовником та іншими сторонами процесу
• Проєктувати технічні рішення та керувати їхнім життєвим циклом
• Моделювати бізнес-процеси та розробляти моделі рішень
• Планувати та організовувати тестування рішень замовником
• Підготовку технічної документації (функціональні/нефункціональні вимоги), інструкції користувача

• Підготовку наказів всередині компанії для виконання робіт на IT платформах

   

Яка кваліфікація та досвід необхідні

• Досвід роботи на посаді бізнес або системного аналітика в IT проєктах від 2-х років
• Розуміння REST-архітектури, основ СУБД
• Професійне знання нотації UML
• Досвід роботи з Jira, Confluence
• Базові навички роботи з SQL запитами
• Досвід роботи з проєктами з використанням ШІ
• Аналітичне мислення, вміння збирати, формалізувати та документувати бізнес-вимоги в рамках проєкту/завдання
• Навички проектного менеджменту, контроль за дедлайнами проєктів

Плюсом стане

• Знання BPMN
• Знання MS Project
• Досвід роботи з системами типу Billing, DWH та інші
• Досвід роботи з Power BI
• Досвід роботи розробки та інтеграцій з векторними базами даних

Ми пропонуємо

• Офіс або ремоут — вирішувати тобі. Ми даємо можливість працювати будь-де, а робоче місце облаштуємо
• Ремоут онбординг
• Перформанс бонуси для всіх (річні чи квартальні — залежить від ролі)
• Навчаємо працівників: є безліч внутрішніх ресурсів і програм від партнерів, власна бібліотека
• Страхування здоров’я і життя для працівників
• Wellbeing-програма та корпоративний психолог
• Компенсація витрат на мобільний зв’язок Київстар

Ми шукаємо стратегічного ІТ-лідера з глибоким практичним досвідом роботи з Microsoft технологіями (Azure, M365, Active Directory, Power Platform, Dynamics, тощо), який здатен формувати архітектуру корпоративних сервісів відповідно до бізнес-цілей. Якщо ти вмієш поєднувати аналітику, технічну експертизу та лідерство, вмієш будувати масштабні ІТ-сервіси, динамічно організовувати та вести за собою команди — ця роль для тебе.

Що ти будеш робити

• Бути головним ІТ-партнером для замовника: відповідати за всі технічні рішення, розвиток ІТ-ландшафту, консультувати бізнес щодо технологічних можливостей
• Проєктувати та впроваджувати архітектуру для:

          - гібридної інфраструктури на базі Azure + on-prem

          - інтеграції Microsoft 365 сервісів (Exchange Online, Teams, SharePoint)

          - побудови Zero Trust моделі з використанням Azure AD, Conditional Access, Defender

• Керувати розвитком сервісів: створення backlog, пріоритезація, контроль реалізації, участь у релізах
• Проводити аудит існуючих рішень, виявляти технічний борг, пропонувати оптимізації
• Організовувати роботу команд: постановка задач, контроль якості, менторинг, участь у співбесідах
• Вести технічні переговори з постачальниками, брати участь у тендерах, оцінювати TCO/ROI
• Забезпечувати відповідність архітектури вимогам безпеки, надійності, масштабованості
• Формувати архітектурну документацію, шаблони, стандарти, гайдлайни

Яка кваліфікація та досвід необхідні

• Досвід управління ІТ-командами та проєктами з архітектурним компонентом
• Глибоке розуміння корпоративної ІТ-архітектури
• Знання процесів управління життєвим циклом сервісів
• Навички переговорів та роботи з постачальниками
• Стратегічне мислення, аналітичність, лідерські якості
• Англійська — на рівні, достатньому для участі в технічних мітингах, листуванні та презентації рішень

Що ми пропонуємо

• Вплив на стратегічні рішення компанії замовника
• Роботу з масштабними трансформаційними проєктами
• Можливість будувати архітектуру з нуля або трансформувати існуючу
• Професійне середовище, де цінують експертизу та ініціативу
• Гібридний формат роботи, гнучкість, підтримка розвитку
• Перформанс бонуси для всіх (річні чи квартальні — залежить від ролі)
• Навчаємо працівників: є безліч внутрішніх ресурсів і програм від партнерів, власна бібліотека
• Страхування здоров’я і життя для працівників
• Wellbeing-програма та корпоративний психолог
• Компенсація витрат на мобільний зв’язок Київстар

Київстар.Тех відкриває нову вакансію у департаменті систем взаємодії з клієнтами.

Про нас

Kyivstar.Tech — українська гібридна ІТ-компанія, резидент Дія.City. Ми є дочірньою компанією Київстар, одного з найбільших українських операторів зв’язку.

Наша місія — змінювати життя в Україні та у світі, створюючи технологічні рішення і продукти, що реалізують потенціал компаній і потреби користувачів.

Понад 600 спеціалістів KS.Tech щодня працюють у різних сферах: мобільні та веб-рішення, а також проєктування, розробка, підтримка та технічне обслуговування високопродуктивних систем і сервісів.

Ми віримо в інновації, що дійсно приносять якісні зміни, та постійно кидаємо виклик традиційним підходам і рішенням. Кожен з нас є адептом підприємницької культури, яка дозволяє ніколи не зупинятися, розвиватися і створювати нове.

Що ти будеш робити

• Аналізувати бізнес-потреби внутрішнього/зовнішнього замовника, з врахуванням можливих обмежень та розробкою архітектурних рішень
• Експертну оцінку проєктної документації замовника (брифи, концепції, інше)
• Узгоджувати вимоги між внутрішнім/зовнішнім замовником та іншими сторонами процесу
• Проєктувати технічні рішення та керувати їхнім життєвим циклом
• Моделювати бізнес-процеси та розробляти моделі рішень
• Планувати та організовувати тестування рішень замовником
• Підготовку технічної документації (функціональні/нефункціональні вимоги), інструкції користувача

• Підготовку наказів всередині компанії для виконання робіт на IT платформах

   

Яка кваліфікація та досвід необхідні

• Досвід роботи на посаді бізнес або системного аналітика в IT проєктах від 1-uj рокіe
• Розуміння REST-архітектури, основ СУБД
• Досвід роботи з Jira, Confluence
• Базові навички роботи з SQL запитами
• Досвід роботи з проєктами з використанням ШІ
• Аналітичне мислення, вміння збирати, формалізувати та документувати бізнес-вимоги в рамках проєкту/завдання
• Навички проектного менеджменту, контроль за дедлайнами проєктів

Плюсом стане

• Знання BPMN

• Знання MS Project

   

Ми пропонуємо

• Офіс або ремоут — вирішувати тобі. Ми даємо можливість працювати будь-де, а робоче місце облаштуємо
• Ремоут онбординг
• Перформанс бонуси для всіх (річні чи квартальні — залежить від ролі)
• Навчаємо працівників: є безліч внутрішніх ресурсів і програм від партнерів, власна бібліотека
• Страхування здоров’я і життя для працівників
• Wellbeing-програма та корпоративний психолог
• Компенсація витрат на мобільний зв’язок Київстар

Вимоги до володіння мовами

English

A2 - Елементарний

Ukrainian

Носій мови