N-iX

We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

N-iX is looking for a Middle Data Engineer for 6 months' engagement. 

You will act as the independent hands-on engineer and the technical owner of data readiness. The role combines pipeline and query engineering with investigation of source, mapping, hierarchy, and validation issues; coordination of market and provider validation cycles; reconciliation of outputs; and delivery of technically ready datasets to downstream consumers.

The Data Engineering team builds and maintains pipelines, while mappings and configurations determine cell/model scope; Snowflake extraction jobs run SQL through Databricks, with Blob Storage, validation, Medallion transformations, Power BI review, and Gold delivery to Ekimetrics. The operating model also requires end-to-end triage across MDFA, CDF, WPP, Data Foundation, Redmill, and market stakeholders rather than treating every discrepancy as a coding defect.

Key responsibilities:

• Independently design, develop, maintain, test, deploy, and optimize ingestion, validation, transformation, aggregation, data-quality, anomaly-detection, and extraction workflows
• Develop and tune Python/PySpark packages, SQL extraction queries, Databricks jobs, ADF pipelines, Delta tables, and source-to-target contracts
• Own technical readiness for new cells and refreshes: clarify filters and expected scope, implement or update queries, review mappings/configuration, reconcile outputs, and confirm readiness for business validation
• Investigate source, NCID, taxonomy, hierarchy, mapping, naming-convention, aggregation, missing-week, outlier, and performance issues across CDF, MDFA/PFME, APIs, manual files, and specific sources
• Coordinate technical validation cycles with Product, CMIA/markets, WPP/MDFA, CDF, other data providers, and Ekimetrics; convert reported discrepancies into actionable owners and technical evidence
• Drive complex incident resolution across pipelines, data contracts, access, service principals, secrets, networking, Power BI refreshes, and downstream delivery
• Review pull requests and test evidence; guide the Junior engineer and delegate scoped engineering/support work without becoming a people manager
• Maintain architecture documentation, interface contracts, repository documentation, runbooks, deployment procedures, and support/escalation guidance

• Recommend practical automation, reliability, performance, and maintainability improvements while respecting platform standards and business-validation ownership.

   

Must-have technical competencies:

• 5–6 years’ professional engineering experience with independent production ownership
• Strong Python, PySpark, and SQL, including complex transformations, query optimization, reusable packages, debugging, tests, and reconciliation
• Strong ETL/ELT and batch-pipeline engineering across relational warehouses, APIs, object storage, and file-based ingestion
• Experience with a cloud data lake/lakehouse, Medallion patterns, schema/interface contracts, data-quality controls, orchestration, observability, and incident recovery
• Solid Git engineering practices: branching, pull requests, reviews, automated tests, deployment controls, and documentation
• Proven ability to translate business/data requirements into filters, mappings, transformations, validation rules, and operational workflows

• Stakeholder-facing problem solving: explain discrepancies, challenge incomplete requirements, establish technical owners, and drive issues to closure.

   

Nice-to-have:

• Strong preference for Azure Data Factory, Azure Databricks, Databricks Jobs/API, Delta Lake, Snowflake, Azure Blob Storage/Data Lake, Power BI, GitHub, and Azure Key Vault
• Valuable experience with Pandera or equivalent schema-validation frameworks, Streamlit, Managed Identity/service principals, Azure Communication Services, Managed VNet/Private Endpoints, and Dev/Prod release practices
• Experience with PFME/media data, syndicated sales, marketing hierarchies, MMM inputs, or multi-market data onboarding is preferred but can be learned.

N-iX is looking for a Junior Data Engineer to join a data-focused team supporting the day-to-day operations and ongoing development of enterprise data solutions. This is a 6-month engagement with an opportunity to gain hands-on experience working with modern cloud data platforms, large-scale datasets, and production data pipelines.

You will work closely with experienced Data Engineers, contributing to pipeline maintenance, troubleshooting, onboarding new data sources, and implementing well-defined enhancements across the data platform. This role is ideal for engineers with 1-2 years of professional experience who want to deepen their expertise in data engineering and cloud technologies.

About the Role

As a Junior Data Engineer, you will help ensure the reliability and quality of data pipelines that support business-critical analytics and reporting. You'll participate in monitoring, troubleshooting, testing, and implementing data processing logic while following established engineering standards and delivery practices.

Under the guidance of senior team members, you will contribute to data ingestion processes, validation activities, technical documentation, and operational support, gaining exposure to modern technologies such as Azure, Databricks, PySpark, and Snowflake.

Responsibilities

• Monitor and support scheduled and event-driven data pipelines, data processing jobs, reporting refreshes, and data quality checks.
• Execute standard data ingestion and refresh activities from multiple sources, including APIs, CSV files, syndicated datasets, and configuration inputs.
• Implement well-defined Python, PySpark, and SQL changes, including new filters, transformations, mappings, validation rules, and minor pipeline enhancements.
• Perform schema validation, reconciliation checks, regression testing, and source-to-target data verification.
• Investigate pipeline failures, validation issues, missing data, rejected files, and reporting discrepancies.
• Troubleshoot first-line operational incidents using logs, job outputs, and monitoring tools.
• Escalate complex technical or business-data issues with clear diagnostic information and supporting evidence.
• Maintain technical documentation, deployment notes, runbooks, configuration files, and operational records.
• Follow established engineering practices, including Git workflows, pull requests, code reviews, testing, and deployment procedures.

• Support onboarding of new data sources and contribute to continuous improvement initiatives.

   

Requirements

• 1-2 years of professional experience in Data Engineering, ETL/ELT development, Analytics Engineering, or Data Support roles.
• Good working knowledge of Python and SQL.
• Understanding of data pipelines, data transformations, batch processing, and ETL/ELT concepts.
• Familiarity with relational databases and data warehouse concepts.
• Experience working with API integrations and file-based data processing (CSV, Parquet, etc.).
• Hands-on experience with Git, version control workflows, pull requests, and code reviews.
• Understanding of data quality principles, including validation, reconciliation, schema checks, and error handling.
• Ability to analyze logs, troubleshoot issues, and communicate findings clearly.
• Strong analytical and problem-solving skills.

• Intermediate or higher English level

  .

Nice to Have

• Experience with Azure Data Factory, Azure Databricks, PySpark, Snowflake, Delta Lake, Azure Data Lake Storage, or similar cloud data technologies.
• Exposure to modern data platform architectures, including Medallion (Bronze-Silver-Gold) data processing patterns.
• Familiarity with Power BI or other BI/reporting platforms.
• Knowledge of cloud environments and DevOps practices.
• Experience with data validation frameworks such as Pandera.

• Understanding of CI/CD pipelines and deployment processes.

   

What Makes You a Great Fit

• You enjoy working with data and solving technical problems.
• You are detail-oriented and take ownership of the quality of your work.
• You are comfortable working within established processes while continuously learning new technologies.
• You communicate clearly and collaborate effectively with technical and non-technical stakeholders.
• You are proactive, curious, and eager to grow your data engineering skills in a production environment.

N-iX is looking for a Middle Data engineer for 6 months' engagement. 

You will act as the independent hands-on engineer and the technical owner of data readiness. The role combines pipeline and query engineering with investigation of source, mapping, hierarchy, and validation issues; coordination of market and provider validation cycles; reconciliation of outputs; and delivery of technically ready datasets to downstream consumers.

The Data Engineering team builds and maintains pipelines, while mappings and configurations determine cell/model scope; Snowflake extraction jobs run SQL through Databricks, with Blob Storage, validation, Medallion transformations, Power BI review, and Gold delivery to Ekimetrics. The operating model also requires end-to-end triage across MDFA, CDF, WPP, Data Foundation, Redmill, and market stakeholders rather than treating every discrepancy as a coding defect.

Key responsibilities:

• Independently design, develop, maintain, test, deploy, and optimize ingestion, validation, transformation, aggregation, data-quality, anomaly-detection, and extraction workflows
• Develop and tune Python/PySpark packages, SQL extraction queries, Databricks jobs, ADF pipelines, Delta tables, and source-to-target contracts
• Own technical readiness for new cells and refreshes: clarify filters and expected scope, implement or update queries, review mappings/configuration, reconcile outputs, and confirm readiness for business validation
• Investigate source, NCID, taxonomy, hierarchy, mapping, naming-convention, aggregation, missing-week, outlier, and performance issues across CDF, MDFA/PFME, APIs, manual files, and specific sources
• Coordinate technical validation cycles with Product, CMIA/markets, WPP/MDFA, CDF, other data providers, and Ekimetrics; convert reported discrepancies into actionable owners and technical evidence
• Drive complex incident resolution across pipelines, data contracts, access, service principals, secrets, networking, Power BI refreshes, and downstream delivery
• Review pull requests and test evidence; guide the Junior engineer and delegate scoped engineering/support work without becoming a people manager
• Maintain architecture documentation, interface contracts, repository documentation, runbooks, deployment procedures, and support/escalation guidance
• Recommend practical automation, reliability, performance, and maintainability improvements while respecting platform standards and business-validation ownership.

Must-have technical competencies:

• 5–6 years’ professional engineering experience with independent production ownership
• Strong Python, PySpark, and SQL, including complex transformations, query optimization, reusable packages, debugging, tests, and reconciliation
• Strong ETL/ELT and batch-pipeline engineering across relational warehouses, APIs, object storage, and file-based ingestion
• Experience with a cloud data lake/lakehouse, Medallion patterns, schema/interface contracts, data-quality controls, orchestration, observability, and incident recovery
• Solid Git engineering practices: branching, pull requests, reviews, automated tests, deployment controls, and documentation
• Proven ability to translate business/data requirements into filters, mappings, transformations, validation rules, and operational workflows
• Stakeholder-facing problem solving: explain discrepancies, challenge incomplete requirements, establish technical owners, and drive issues to closure.

Nice-to-have:

• Strong preference for Azure Data Factory, Azure Databricks, Databricks Jobs/API, Delta Lake, Snowflake, Azure Blob Storage/Data Lake, Power BI, GitHub, and Azure Key Vault
• Valuable experience with Pandera or equivalent schema-validation frameworks, Streamlit, Managed Identity/service principals, Azure Communication Services, Managed VNet/Private Endpoints, and Dev/Prod release practices
• Experience with PFME/media data, syndicated sales, marketing hierarchies, MMM inputs, or multi-market data onboarding is preferred but can be learned.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are looking for a Agentic UX/Converation Designer to join our team!

Our client is Azerbaijani telecommunications company and the largest mobile network operator in Azerbaijan. The main products are: Fixed telephony, Mobile telephony, Internet services, Wireless broadband, and Value-added services. The primary goal is to accelerate the client’s Data & AI initiatives via a secure, hybrid cloud foundation on AWS while systematically modernizing the IT estate as part of the AWS MAP 2.0 program.

Key Project Objectives include:

• Cloud Foundation & Landing Zone: Deploy target hybrid network architectures, establishing a secure AWS Landing Zone Accelerator (LZA) and hybrid Data/AI platforms on AWS.
• Security, Compliance & Sovereignty: Operationalize on-premises data de-identification and Format Preserving Encryption (FPE) tokenization (achieving zero raw PII in the cloud), fully adhering to Azerbaijani Personal Data Law No. 998-IIIQ and Critical Information Infrastructure Rules (Resolution No. 229).
• AI Chatbot & Real-Time Voicebot Implementation: Develop and operationalize a flagship Customer Care Voicebot (STT → LLM → TTS pipeline) and Agentic Chatbot targeting < 2.0s conversational voice latency and ~200 rps throughput as the first hybrid-setup consumer.

Responsibilities:

• Lead end-to-end conversational UX and dialogue design for the client’s flagship Customer Care Voicebot and Agentic Chatbot across speech (Avaya) and digital channels (Genesys, Mobile App).
• Define, document, and refine conversational voice personas, turn-taking behavior, barge-in rules, fallback strategies, and human-agent escalation logic across all customer care journeys.
• Craft, test, and optimize prompt engineering strategies for conversational LLMs/SLMs (Amazon Bedrock, SageMaker) specifically tuned for spoken interactions and multi-turn dialogue in Azerbaijani.
• Map multi-agent supervisor/specialist hand-off workflows, intent routing logic, tool invocation contracts (MCP gateways / APIs), and RAG knowledge base retrieval paths in close collaboration with AI Engineers and Architects.
• Partner with Business Analysts, Contact Center SMEs, and CVM teams to integrate offer decisioning contracts, CVM uplift model scores, and Next-Best-Offer (NBO) campaign outputs directly into bot dialogue decision layers.
• Establish dialogue NFR baselines, user experience acceptance criteria, and quality metrics to help guarantee round-trip conversational voice latency < 2.0 seconds.
• Perform prompt engineering, regression testing, and evaluation harness benchmarking for prompt/agent version updates using Amazon Bedrock AgentCore and prompt management tools.
• Collaborate with data labeling and customer care teams to review call/chat transcriptions, analyze intent drop-offs, dialect edge cases, and dissatisfaction signals to continuously iterate dialogue flows.
• Design guardrails, content safety mechanisms, and privacy-compliant interaction flows (ensuring zero raw PII exposure and full adherence to Azerbaijani Personal Data laws).
• Support User Acceptance Testing (UAT), regression testing, and production hypercare for customer care conversational AI flows within the program's Work Breakdown Structure (WBS).

Requirements:

• 3+ years of hands-on experience as a Conversation Designer, Agentic UX Designer, Voice UX Designer, or Technical Business Analyst specializing in conversational AI, voicebots, and chatbots.
• Strong domain knowledge of real-time voicebot/chatbot architecture, including STT (Speech-to-Text / Whisper ASR), LLM dialogue orchestration, and TTS (Text-to-Speech) pipelines.
• Deep expertise in dialogue flow mapping, prompt engineering for spoken LLM interactions, voice persona design, turn-taking, barge-in behavior, and fallback/escalation logic.
• Solid understanding of generative AI agent frameworks, multi-agent orchestration (supervisor/specialist hierarchies), RAG retrieval flows, and tool/action contracts (Model Context Protocol / MCP gateways, APIs).
• Practical experience with contact center and telephony platform integrations (Avaya voice telephony, Genesys omnichannel chat, mobile app interfaces).
• Hands-on experience with prompt testing, prompt versioning, evaluation harnesses, and LLM benchmarking tools (e.g., Bedrock AgentCore, PromptOps, MLflow, or custom evaluation frameworks).
• Strong capability as a technical business analyst—translating business requirements, CVM campaign rules, and contact center KPIs into actionable technical dialogue specifications.
• Familiarity with data privacy standards, PII masking, guardrails, and content safety in conversational interfaces.

Nice to have:

• Experience with AWS AI services and platforms (Amazon Bedrock AgentCore, SageMaker, Bedrock Guardrails, Knowledge Bases).
• Experience in Azerbaijani or Turkic language NLP, speech nuances, and dialectical speech data processing.
• Experience with CVM (Customer Value Management) offer decisioning, propensity/churn models, and Next-Best-Action (NBA) integration in customer care channels.
• Experience in telecom domain customer care processes, IVR tree migration, and agent-assist workflows.

Soft Skills & Team Fit:

• Excellent analytical, communication, and stakeholder management skills to articulate complex technical concepts to business and engineering teams alike.
• Strong user empathy with a passion for designing natural, efficient, and engaging conversational user experiences.
• Proactive mindset with strong ownership within an Agile / Scrum framework and WBS-driven delivery cadences.
• Upper-Intermediate+ English level (written and spoken).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Position Overview:
We are seeking an experienced and highly skilled Senior Business Analyst to join our team in a leading pharmaceutical company. This role will focus on supporting data-driven and AI-powered initiatives that enhance decision-making, operations, and advanced analytics.

The ideal candidate should have a strong analytical background and the ability to translate business needs into actionable insights and requirements for both AI-driven products.

This is an opportunity to work in a Fortune 500 company, contribute to life-changing projects at the intersection of data and artificial intelligence, and collaborate with a team of experts in a fast-paced, innovation-focused environment. You will be an integral part of a mission that aims to enhance healthcare outcomes through advanced analytics and AI innovation.

Key Responsibilities:

• Collaborate closely with cross-functional teams, including data scientists, product managers, and data engineers, to understand business objectives and identify data and AI opportunities.
• Conduct thorough requirements analysis for AI-centric projects, including gathering, documenting, and validating requirements to support product design and development.
• Own end-to-end documentation — user stories, functional specifications, and AI/data workflows — ensuring consistency and traceability throughout the project lifecycle.
• Participate in data governance, quality, and compliance initiatives, ensuring the accuracy, integrity, and ethical use of data in AI models and analytics.
• Work with stakeholders to understand business goals and translate them into actionable requirements.
• Act as a liaison between business users and technical teams, ensuring clear communication and alignment.
• Actively participate in testing and validating deliverables— AI models and product features—ensuring outputs meet business requirements, are user-friendly, and align with compliance standards before launch.
•  

Qualifications:

• 5+ years of experience as a Business Analyst with exposure to AI-focused projects.
• Proven ability to independently lead requirements definition for AI/ML projects(e.g., predictive analytics, NLP solutions, intelligent automation etc.) from inception through delivery.
• Strong track record managing complex stakeholder landscapes, including senior leadership, in fast-moving environments.
• Ability to support and execute testing of deliverables (e.g., user acceptance testing, functional validation), ensuring high-quality outcomes.
• Experience with data governance, data quality, and data privacy compliance within regulated industries is a plus.
• Excellent communication skills with the ability to translate complex technical details, including AI concepts, into business language for stakeholders.
• Highly organized and detail-oriented, with strong problem-solving skills.
• Strong analytical skills.
• Familiarity with data visualization and reporting tools (e.g., Tableau, Power BI) is a plus.
• Basic understanding of SQL or data querying, though not required to perform data engineering tasks.

We are looking for a Senior Data Engineer to join a strategic marketing technology (Martech) transformation initiative for a large enterprise organization. The project focuses on modernizing the client's marketing data platform, rebuilding data pipelines, and improving marketing attribution across multiple business brands.

As part of a dedicated data engineering team, you will help build a scalable, cloud-native data platform on Google Cloud Platform (GCP), enabling better visibility into marketing performance and supporting data-driven decision making. This is engagement through the end of 2026, working closely with the client's Data Engineering, Product, and Martech teams.

Responsibilities:

• Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).
• Build and optimize data models in BigQuery to support analytics and marketing reporting.
• Rebuild legacy marketing data pipelines following modern engineering best practices and enterprise standards.
• Contribute to the development of a canonical enterprise data model and semantic data layer.
• Support the implementation and adoption of DataHub as the enterprise data catalog.
• Develop automated CI/CD pipelines for data engineering workflows and enforce coding and data quality standards.
• Ensure proper data isolation between multiple business brands while enabling consolidated reporting where appropriate.
• Collaborate closely with Product Managers, Martech specialists, Analytics teams, and other data engineers to deliver business value.
• Optimize data processing performance, reliability, monitoring, and cost efficiency.

Required Qualifications:

• 5+ years of experience as a Data Engineer.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Advanced experience with BigQuery.
• Strong SQL and Python development skills.
• Experience designing and implementing modern ELT/ETL pipelines.
• Solid understanding of dimensional modeling, semantic modeling, and enterprise data architecture.
• Experience building production-grade CI/CD pipelines for data platforms.
• Familiarity with Git and modern software engineering best practices.
• Strong communication skills and ability to work within cross-functional teams.
• Upper-Intermediate or higher English.

Nice to Have:

• Experience with marketing technology (Martech) platforms and marketing attribution.
• Hands-on experience integrating: Google Ads, Google Analytics (GA4), Search Ads 360 (SA360), Campaign Manager 360, DV360
• Experience with DataHub or similar data catalog solutions.
• Experience implementing semantic layers for analytics platforms.
• Understanding of multi-brand or multi-tenant data architectures.
• Experience modernizing legacy data platforms and rebuilding pipelines from scratch.

N-iX is looking for Lead .Net Engineer to join the team

Position Overview:  

As a .NET Engineer you will drive the technical modernization of a large-scale system from .NET Framework 4.8 to .NET 10. Your work will span the full backend stack — replacing Windows-only dependencies, refactoring legacy patterns, migrating data access to EF Core, and ensuring every service is portable, containerizable, and ready for AWS cloud deployment. You will collaborate closely with DevOps and database engineers as part of a cross-functional Agile team delivering a phased, production-safe migration.

Responsibilities:

• Migrate a .NET Framework 4.8 application to .NET 10.
• Migrate a large database-first Entity Framework 6 model to EF Core 8 across multiple bounded contexts, one domain at a time.
• Identify and replace Windows-only libraries and assembly references that prevent building and running on Linux.
• Establish unit test coverage measurement and enforce quality gates as part of the migration pipeline.
• Collaborate with the DevOps engineer on Dockerfile authoring, environment configuration, and secrets injection.
• Participate in Agile/SCRUM processes, conduct code reviews, and document migration decisions.

Must-Have Qualifications:

• 5+ years of C# and .NET backend development with strong knowledge of ASP.NET and ASP.NET Core.
• Proven, hands-on experience migrating .NET Framework applications to .NET Core / .NET 10 in production.
• Solid experience with Entity Framework Core.
• Solid knowledge of DDD, CQRS, and repository patterns in layered .NET architectures.
• Familiarity with Docker multi-stage builds and Linux container fundamentals for .NET applications.
• Proficient with xUnit and Moq for unit testing; comfortable with container-wired test setups.
• Experience with AWS ECS / Fargate and ECR for deploying containerized .NET applications.
• Familiarity with MassTransit and RabbitMQ or Amazon MQ for event-driven messaging.
• Experience with Hangfire or similar background job processing frameworks.
• Proficient in Git and familiar with Agile/SCRUM team processes.
• Upper-Intermediate/Advanced English level 

Nice-to-Have Skills:

• Experience building CI/CD pipelines for .NET projects.
• Familiarity with micro-frontend architecture and Angular-based single-page applications.
• Experience with automated code coverage tooling and enforcing coverage thresholds in CI.
• Experience with performance optimization and scalable enterprise backend systems.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are looking for a Senior AI/ML Engineer to design, develop, and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready machine learning and LLM-based solutions, from understanding business needs and exploring data to designing technical approaches, implementing solutions, and integrating them into Foundry workflows. You will work closely with data engineers, business analysts, and domain experts, contribute to technical decisions, and help establish best practices for building scalable and reliable AI solutions.

Key Responsibilities:

• Design and develop AI/ML solutions for predictive analytics, classification, forecasting, automation, and AI-assisted workflows within Palantir Foundry, leveraging Python, Ontology objects, pipelines, and workflows.
• Design, implement, evaluate, and optimize LLM/NLP and RAG solutions using Palantir AIP, including prompt engineering, embeddings, retrieval strategies, vector search, and text processing.
• Own the end-to-end lifecycle of AI solutions, from experimentation and model development to deployment, monitoring, and continuous improvement.
• Collaborate with data engineers to understand data sources, ensure data quality, and design efficient and scalable data processing approaches.
• Integrate AI solutions into production workflows and optimize them for accuracy, reliability, latency, scalability, and cost-efficiency.
• Contribute to technical architecture and design decisions, including model, framework, and tool selection; proactively identify technical risks, improvement opportunities and proactively propose solutions.
• Work with business and domain stakeholders to translate business needs into practical, scalable, and production-ready AI solutions, clearly communicating technical decisions and model limitations.
• Identify technical risks, limitations, and opportunities for improvement and proactively propose solutions.

Requirements:

• 4+ years of experience in machine learning, AI engineering, applied data science, or related fields.
• Strong Python skills and hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong practical experience with LLMs, NLP, or GenAI applications, including prompt engineering, embeddings, text processing, summarization, or similar use cases.
• Solid hands-on experience designing and implementing RAG architectures, vector databases, and retrieval strategies.
• Strong understanding of the ML lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Experience working with both structured and unstructured data, including tabular data, time series, text, and documents.
• Ability to independently analyze ambiguous problems, propose technical approaches, and drive solutions from concept to implementation.
• Strong communication skills, with the ability to explain AI concepts, technical decisions, and model behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to Have:

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

About the Client:

Our client is a leading global healthcare organization, driving innovation in pharmaceuticals, biotechnology, and patient-centric solutions. We develop advanced data and analytics solutions that help global organizations turn complex data into intuitive digital tools, enabling teams to make informed decisions in their daily operations and long-term strategy. Our projects span modern operational applications, interactive dashboards, and advanced analytics platforms designed to deliver actionable insights across multiple business domains.

About the Role:

We are looking for a Senior Data Analyst to support a project focused on assessing and building a comprehensive customer universe using data from internal and external sources. The role focuses on data acquisition, validation, matching, and process development — assessing data quality and coverage, matching external data with existing customer/account databases, identifying gaps and duplicates, and developing a structured approach for ongoing data maintenance and improvement. The contractor will work closely with Global Insights, Customer Excellence, and local affiliates to refine processes, support pilot readiness, and translate findings into practical recommendations.

Key Responsibilities:

• Support the execution of a data acquisition and validation POC using external data sources.
• Work with large datasets from internal and external sources, including cleansing, structuring, and validating data.
• Assess match rates, data coverage, duplicates, gaps, inconsistencies, and overall data quality.
• Investigate data discrepancies and identify opportunities for data enrichment and improvement.
• Evaluate external data attributes as potential indicators of customer/account size, activity, or potential.
• Develop and document approaches for customer universe identification, matching, validation, and ongoing maintenance.
• Create clear process documentation and SOPs and identify opportunities for process simplification or automation.
• Support pilot preparation by defining relevant requirements, success metrics, and recommendations.
• Collaborate with business stakeholders and local teams to understand requirements and communicate findings.
• Present analytical findings and practical recommendations to relevant stakeholders.
• Maintain project documentation, trackers, and progress updates.

Required Qualifications:

• 4+ years of experience in Data Analytics, Data Quality, Data Operations, Business Analysis, or a related field.
• Strong hands-on experience working with large and complex datasets.
• Advanced Excel skills and confidence working with large volumes of data.
• Practical experience with data cleansing, validation, matching, and deduplication.
• Experience combining and analyzing data from multiple sources.
• Strong analytical and problem-solving skills, with the ability to investigate data quality issues and identify patterns, gaps, and inconsistencies.
• Ability to independently structure ambiguous problems and develop practical approaches to solving them.
• Ability to translate analytical findings into clear business insights and recommendations.
• Strong attention to detail and data accuracy.
• Good communication and stakeholder management skills.
• Ability to work independently and take ownership of tasks in a fast-moving environment.

Nice to have:

• Experience in healthcare, aesthetics, medical devices, pharmaceuticals, or commercial excellence.
• Experience using external data providers or web-sourced datasets.
• Experience with CRM systems (Veeva CRM, Salesforce, Dynamics, etc.).
• Experience building customer universe or account segmentation approaches.
• Familiarity with data enrichment and data quality methodologies.
• Experience working across international markets.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

Our client is a leading European online car marketplace, connecting car buyers and sellers across the continent. The platform serves over 30 million monthly users and operates across 18 countries, making it one of the largest and most trusted digital marketplaces for vehicles in Europe.

We're looking for a mature, Senior / Lead PHP Engineer with deep Laravel expertise and hands-on experience building or integrating agentic AI systems. Over a 6-month engagement, you will help the team build the next major product release, taking ownership of complex backend features end-to-end, mentoring other engineers, and helping shape how AI-driven automation and agents fit into the product and internal workflows.

You will join the cross-functional product team, working full time in the EDT (Toronto) time zone alongside engineers who value clear communication, independent judgment on ambiguous problems, and production-ready engineering.
 

Responsibilities:

• Design, build, and maintain robust backend services and APIs using PHP and Laravel to deliver the next major product release.
• Own features from technical design through deployment and monitoring.
• Integrate and orchestrate agentic AI workflows (e.g., LLM-based agents, tool-calling pipelines, autonomous task runners) into existing products and internal tooling.
• Improve system performance, reliability, and security across the stack.
• Mentor other engineers and partner with colleagues across functions to move technical topics forward.
• Stay current with the PHP/Laravel ecosystem and emerging agentic AI tools and patterns.

Requirements:

• 6+ years of professional PHP development experience, including 4+ years building applications with Laravel (or comparable modern PHP framework experience with strong Laravel proficiency).
• Hands-on GenAI experience — you've built with LLM APIs, tool/function calling, retrieval, agents, or agent frameworks and put them into real workflows.
• Modern AI coding tools (e.g., Claude Code, Codex) are part of how you work day to day.
• Solid database skills (MySQL/PostgreSQL), including query optimization and schema design.
• Familiarity with containerization (Docker) and cloud deployment (AWS, GCP, or similar).
• Solid engineering fundamentals: testing, debugging, code quality, and getting things production-ready.
• Strong communication and collaboration skills, with the judgment to work independently on ambiguous problems.
• English level: Upper-Intermediate or higher. 

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

N-iX is looking for a Junior Data Engineer to join a data-focused team supporting the day-to-day operations and ongoing development of enterprise data solutions. This is a 6-month engagement with an opportunity to gain hands-on experience working with modern cloud data platforms, large-scale datasets, and production data pipelines.

You will work closely with experienced Data Engineers, contributing to pipeline maintenance, troubleshooting, onboarding new data sources, and implementing well-defined enhancements across the data platform. This role is ideal for engineers with 1-2 years of professional experience who want to deepen their expertise in data engineering and cloud technologies.

About the Role

As a Junior Data Engineer, you will help ensure the reliability and quality of data pipelines that support business-critical analytics and reporting. You'll participate in monitoring, troubleshooting, testing, and implementing data processing logic while following established engineering standards and delivery practices.

Under the guidance of senior team members, you will contribute to data ingestion processes, validation activities, technical documentation, and operational support, gaining exposure to modern technologies such as Azure, Databricks, PySpark, and Snowflake.

Responsibilities

• Monitor and support scheduled and event-driven data pipelines, data processing jobs, reporting refreshes, and data quality checks.
• Execute standard data ingestion and refresh activities from multiple sources, including APIs, CSV files, syndicated datasets, and configuration inputs.
• Implement well-defined Python, PySpark, and SQL changes, including new filters, transformations, mappings, validation rules, and minor pipeline enhancements.
• Perform schema validation, reconciliation checks, regression testing, and source-to-target data verification.
• Investigate pipeline failures, validation issues, missing data, rejected files, and reporting discrepancies.
• Troubleshoot first-line operational incidents using logs, job outputs, and monitoring tools.
• Escalate complex technical or business-data issues with clear diagnostic information and supporting evidence.
• Maintain technical documentation, deployment notes, runbooks, configuration files, and operational records.
• Follow established engineering practices, including Git workflows, pull requests, code reviews, testing, and deployment procedures.
• Support onboarding of new data sources and contribute to continuous improvement initiatives.

Requirements

Must Have

• 1-2 years of professional experience in Data Engineering, ETL/ELT development, Analytics Engineering, or Data Support roles.
• Good working knowledge of Python and SQL.
• Understanding of data pipelines, data transformations, batch processing, and ETL/ELT concepts.
• Familiarity with relational databases and data warehouse concepts.
• Experience working with API integrations and file-based data processing (CSV, Parquet, etc.).
• Hands-on experience with Git, version control workflows, pull requests, and code reviews.
• Understanding of data quality principles, including validation, reconciliation, schema checks, and error handling.
• Ability to analyze logs, troubleshoot issues, and communicate findings clearly.
• Strong analytical and problem-solving skills.
• Intermediate or higher English level.

Nice to Have

• Experience with Azure Data Factory, Azure Databricks, PySpark, Snowflake, Delta Lake, Azure Data Lake Storage, or similar cloud data technologies.
• Exposure to modern data platform architectures, including Medallion (Bronze-Silver-Gold) data processing patterns.
• Familiarity with Power BI or other BI/reporting platforms.
• Knowledge of cloud environments and DevOps practices.
• Experience with data validation frameworks such as Pandera.
• Understanding of CI/CD pipelines and deployment processes.

What Makes You a Great Fit

• You enjoy working with data and solving technical problems.
• You are detail-oriented and take ownership of the quality of your work.
• You are comfortable working within established processes while continuously learning new technologies.
• You communicate clearly and collaborate effectively with technical and non-technical stakeholders.
• You are proactive, curious, and eager to grow your data engineering skills in a production environment.

Overview:

The Growth Platform Team at Raisin is a cross-functional team enabling Marketing and product teams to scale growth initiatives across web and mobile. The team owns core growth capabilities such as marketing integrations, user tracking, experimentation, bonus management, and attribution models, providing reliable services and data foundations that power growth across markets.

 

As part of this team, you’ll work on complex integrations and data-heavy systems, collaborating closely with Marketing and B2C stakeholders. The Growth Platform Team is responsible for the underlying services, data pipelines, and integrations that make growth measurable and scalable. If you enjoy building platform foundations with clear business impact, this team offers a high-impact and highly collaborative environment.

Your Responsibilities:

• Own and deliver features and bug fixes end-to-end following our SDLC process.
• Utilize AI tools intensively to increase our ability and pace to deliver software.
• Follow best practices around our core stack.
• Contribute to improving how we program, test, review, and ship code.
• Flag process gaps and propose pragmatic improvements.
• Provide constructive code review and solve complex problems together.
• Quickly build practical depth in Growth Platform Team domains.
• Contribute meaningfully to new feature design and implementation.
• Collaborate with Product, Tech Lead, frontend, and data colleagues on contracts and acceptance criteria.

Your Profile:

• Degree in Computer Science, Software Engineering, or equivalent practical experience, with 3 to 5 years of professional backend engineering experience.
• Strong production experience in Python, with hands-on expertise in FastAPI (or equivalent frameworks like Flask/Django REST) and relational databases like MySQL (using SQLAlchemy or similar ORM).
• Demonstrated experience building and running resilient REST APIs and

complex business/financial logic.

• Hands-on experience developing logic for user eligibility, marketing attribution, or automated payout/commission rules is a strong plus.
• Comfortable making reviewed UI updates in TypeScript / React / Next.js
• Practical familiarity with AWS core services (ECS, S3, Secrets Manager) and standard engineering tooling (Git, CI/CD, pytest, Jira, Scrum).
• Strong collaborative approach, fluent in English, and comfortable operating as an Individual Contributor focused on execution.

Nice to Have:

• Experience with Docker, Terraform, Kafka, or feature flag management.
• Experience with Content Management Systems (e.g., Contentstack) or prior fintech/marketplace background.
• German language skills.

We are looking for a Voice AI Engineer (Real-time speech) to join our team! 

Our client is an Azerbaijani telecommunications company and Azerbaijan's largest mobile network operator. The main products are: Fixed telephony, Mobile telephony, Internet services, Wireless broadband, and Value-added services. The primary goal is to accelerate the client’s Data & AI initiatives via a secure, hybrid cloud foundation on AWS while systematically modernizing the IT estate as part of the AWS MAP 2.0 program.

Key Project Objectives include:

• Cloud Foundation & Landing Zone: Deploy target hybrid network architectures, establishing a secure AWS Landing Zone Accelerator (LZA) and hybrid Data/AI platforms on AWS.
• Security, Compliance & Sovereignty: Operationalize on-premises data de-identification and Format Preserving Encryption (FPE) tokenization (achieving zero raw PII in the cloud), fully adhering to Azerbaijani Personal Data Law No. 998-IIIQ and Critical Information Infrastructure Rules (Resolution No. 229).
• AI Chatbot & Real-Time Voicebot Implementation: Develop and operationalize a flagship Customer Care Voicebot (STT → LLM → TTS pipeline) and Agentic Chatbot targeting < 2.0s conversational voice latency and ~200 rps throughput as the first hybrid-setup consumer.

Responsibilities:

• Design, build, and operationalize end-to-end real-time STT → LLM → TTS (Speech-to-Text / LLM / Text-to-Speech) voicebot pipelines on AWS, optimizing for streaming speech-to-text, first-token LLM generation, and first-audio TTS synthesis.
• Deploy and maintain production customer-trained Whisper (Azerbaijani ASR) and Azerbaijani TTS models as low-latency real-time endpoints on Amazon SageMaker and specialized GPU node pools (NVIDIA A100/L40S).
• Implement and manage the Bedrock Proxy Gateway on EKS for multi-model routing, priority queuing via Redis Sorted Sets, cost caps, and high-availability serving targeting ~200 rps without API throttling.
• Integrate voicebot and chatbot decision engines with core enterprise telephony and CVM platforms, including Avaya (voice telephony), Genesys (digital chat/omnichannel), and Pelatro (CVM offer decisioning and uplift models).
• Establish LLMOps & MLOps pipelines using Amazon SageMaker Pipelines and MLflow for experiment tracking, model versioning, prompt/agent registries, automated evaluation harnesses, and RAG knowledge base retrieval.
• Build call and chat transcription pipelines to ingest, transcribe, and extract real-time insights (churn risk, dissatisfaction, intent, lead signals) into downstream decision layers.
• Enforce data sovereignty and privacy controls by integrating on-premises Format Preserving Encryption (FPE) and tokenization wrappers into ML pipelines so zero raw PII enters AWS cloud environments.
• Define NFR baselines, dialogue flows, voicebot persona, turn-taking, and fallback/escalation logic to guarantee conversational round-trip latency < 2.0 seconds.
• Automate ML deployment workflows using GitLab CI/CD and Infrastructure-as-Code (Terraform or AWS CDK), establishing observability and FinOps spend/anomaly monitoring via Amazon CloudWatch and Splunk.

Requirements:

• 4+ years of hands-on experience with machine learning and Speech Processing with a primary focus on real-time conversational AI, ASR (STT), and TTS voice pipelines.
• Deep expertise with Amazon SageMaker (real-time GPU inference endpoints, Pipelines, Feature Store, Model Registry) and Amazon Bedrock (AgentCore, Bedrock Guardrails, Knowledge Bases).
• Proven track record in streaming speech inference, speech synthesis, and low-latency audio processing.
• Strong experience in GPU optimization and containerized orchestration (NVIDIA A100/L40S, AWS EC2 GPU instances, Docker, Kubernetes/EKS).
• Solid understanding of contact center and telephony platform integrations (Avaya, Genesys) and real-time decisioning interfaces.
• Proficient in Python, Redis (priority queuing & caching), and data security/privacy (FPE tokenization, handling sensitive/PII data).

Nice-to-have skills:

• AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect.
• Hands-on experience with EMR-on-EKS, Apache Iceberg, or MSK (Kafka) streaming pipelines.

Soft Skills & Team Fit:

• Strong critical thinking, problem-solving, and analytical skills with ownership of mission-critical, low-latency deliverables.
• Excellent communication and collaboration skills to work closely with cross-functional teams (AI Architects, Data Engineers, CC SMEs, and Security/Compliance).
• Results-oriented, proactive mindset with strong ownership within an Agile / Scrum framework.
• Upper-Intermediate+ English level (written and spoken).

We are looking for a Senior Java Full Stack Engineer with React to join our team!

Our client is one of the world's largest fashion retailers, selling in 215 markets through its online platform or its 6,477 stores in 95 markets. We work closely together as a single company globally focused on the key elements of fashion production – design, manufacture, distribution, and retail. All production is founded on three pillars – flexibility, digital integration, and sustainability.

Responsibilities:

• Participate actively and constantly in the design and development of APIs
• Ensure the availability and resilience of services that help the development of the company’s business.
• Ensure the quality of development and code cleanliness (Clean Code)
• Continuously perfect our style guides, design, and code patterns as well as our React component library
• Implement the scripts for the automation of the test cases.
• Automatic and manual exploratory execution during development to verify that the acceptance criteria are covered.
• Maintain and evolve automated test cases with QA.
• Work in close contact with the Product Owner and support the technical definition of product backlog items
• Guarantee continuous deployment; write qualitative, maintainable code with extensive test coverage in a fast-paced professional software engineering environment
• Suggest technical and functional improvements to add value to the product

Requirements:

• 5+ years of extensive Java development experience, Maven
• 2-3 years of Spring Framework and building Spring web applications
• Understanding and experience developing and deploying microservices
• Experience developing REST interfaces, OpenAPI
• Frontend testing and performance optimization
• CSS3/SCSS/HTML5, modern responsive design techniques
• Extensive experience with ES6, React, Redux, Redux-Saga, TypeScript, CSS, RESTful APIs
• Excellent design, coding, and debugging skills
• OOP, OOD, DDD. Proficient in design patterns
• Working knowledge of relational databases, NoSQL technologies – MongoDB
• Working knowledge of Kafka, Kafka streaming (can be optional)
• Experience with different clouds – AWS, Azure
• Working knowledge of OpenShift, Kubernetes
• Familiar with Graylog, Grafana
• Working experience in an Agile environment, a clear understanding of the Agile methodology mindset, and development practices applicable to it
• Excellent communication, organizational, and facilitation skills, product-oriented mindset, focus on team results, willingness to continuous personal and team improvements, leadership qualities, and resilience.
• Upper-Intermediate/Advanced English level (there will be a lot of communication with the client)

We offer:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team-building