Jobs ML / AI

Description

About the Role
You will be part of the Engineering team, driving the evolution of Batch AI, our AI-powered system that optimizes material feeding in concrete production. Batch AI combines sensor data with predictive and machine learning models to make batching operations more accurate, consistent, and autonomous.
As a Senior ML Engineer, you will apply machine learning engineering and applied data science techniques to design, train, and evaluate models that directly impact industrial performance,
working closely with engineers and the Product Operations team.
This is a hands-on role for someone who thrives on ownership, experimentation, and delivering real-world impact. You will play a key role in advancing the intelligence and reliability of industrial
processes powered by Batch AI.

Requirements:

Qualifications
Must-Have
 

• BSc or MSc in Data Science, Applied Mathematics, Computer Science, or equivalent practical
  experience.
• 5+ years of hands-on experience in applied machine learning, with a focus on regression,
  forecasting, or optimization.
• Proven experience in production-grade ML pipelines, from experimentation to deployment.
• Strong grasp of data science concepts such as cross-validation, quantile modeling, and
  model safeguard techniques.
• Strong background in Python and data science libraries, with the ability to write clean,
  efficient, and production-ready code.
• Experience using modern development tools and practices, including Git and related
  workflows, code review processes, automated testing, and CI/CD pipelines.
• Solid understanding of data lifecycle management, including time-series feature engineering
  and retraining strategies.
• Experience with ML model monitoring, versioning, and continuous retraining frameworks.
• Familiarity with cloud ML ecosystems (Azure or AWS)

• Comfortable documenting and presenting analytical findings to mixed technical and non-technical audiences.

   

  Nice-to-Have

• Experience with Azure ML, CosmosDB, Service Bus, and Kubernetes.
• Experience with AWS SageMaker, ECS Fargate, SQS/EventBridge, and DocumentDB.
• Exposure to industrial data from manufacturing equipment, batching systems, or other IoT-connected process control environments such as manufacturing, logistics, or energy
  sectors.
• Experience applying software development and engineering best practices, including
  architectural, design, and coding principles.

• Experience with containerized workloads (Docker).
   

   

Job responsibilities

•  Design, train, and validate machine learning models that improve process performance and
  stability in concrete batching operations.
• Lead end-to-end model development, from data exploration and feature engineering to deployment and validation.
• Define and implement retraining and validation strategies that ensure continuous performance improvement.
• Work closely with engineers to ensure models integrate efficiently with production systems in Azure and AWS environments.
• Propose data selection and quality control methods to improve training representativity.
• Contribute to the monitoring and evaluation approach for ongoing model health.
• Document methodologies, experiments, assumptions, and decisions to maintain clarity and
  reproducibility.
• Collaborate with team members, the Product Operations team, and other stakeholders as needed to support large-scale deployment.

A fast-growing SaaS company that is changing the way tax, accounting, and auditing firms work, is looking for an ML Engineer to work remotely.

Founded in 2017, the company now has over 350 employees. The company is trusted by over 10,000 firms in more than 25 countries. Its universal platform helps firms manage documents, payments, workflows, and communications more efficiently.

Current tasks to be worked on:

• Text recognition and classification.

• Text matching.

• Document search.

• Creating a basic level (simple working solution), for example, using prompts via a publicly available API to obtain structured output.

The company's mobile app in the App Store has a high rating of 4.9 out of 5.

What the company offers: 30 days of vacation, paid sick leave, training and development budget.

Requirements: experience with classic NLP and modern LLM, RAG, classification tasks.

Experience with document OCR and model tuning would be a plus.

About PICHE

PICHE is Latvia’s leading business park development company with 20 years of experience and over 150 successfully implemented projects in Europe.

We specialize in the development, design, and building of business parks. PICHE is about an improved and organized work environment, so you can focus on what matters most at work.

Ready to lead real change with AI?
Join us and work side by side with one of the company’s top leaders to embed AI into the very core of how we operate — from accounting and procurement to workflow optimization and decision-making. This is a rare opportunity to not only deploy cutting-edge technologies but to shape how an entire organization thinks and works. If you’re passionate about real-world AI applications and want to see your work have a visible business impact — we want to talk to you)

We are currently looking for two specialists to expand our team.

Key Responsibilities:

• Design and implement company-wide strategies for integrating AI into core business operations.
• Partner with various departments to uncover opportunities where AI can streamline and enhance existing processes. 
• Apply machine learning models and smart algorithms customized for specific business use cases.
• Manage the seamless integration of AI tools into the current tech infrastructure. 
• Regularly assess the performance of AI systems to ensure they operate efficiently and reliably. 
• Serve as an internal advisor and mentor on AI topics, helping to build a culture of innovation and AI adoption.
• Stay ahead of industry advancements and embed the latest AI technologies into the company’s strategic plans. 
• Organize and lead internal workshops and training programs to build AI literacy and usage across teams.
   

Your Qualifications:

• Proven experience (1 year+) deploying and integrating AI solutions in real business environments.
• English B2.
• Hands-on experience with automation platforms like n8n, Make, Zapier, or equivalent tools.
• Strong communication skills, with the ability to work effectively across technical and non-technical teams. 

• Solid background in API integration within scalable system architectures.

   

Nice-to-Have Skills:

• Practical experience applying AI/ML in business workflows.
• Experience with automating business processes using AI or large language models (LLMs).
• Proficiency in designing and implementing API integrations and workflow automations. 
• Familiarity with cloud platforms such as AWS, Azure, or GCP for deploying AI solutions.
• Successful involvement in cross-departmental projects combining business and tech teams. 
• Working knowledge of modern LLMs like ChatGPT, Claude, or similar. 
• Background in digital transformation, product development, or innovation-focused roles. 
• Ability to code in Python or other AI-friendly programming languages.
   

We’re happy to provide you with:

• Salary from $1800+tax;
• Fully remote work opportunities;
• Breathtaking challenges, where everything is possible;
• Annual paid leave — 20 working days;
• Paid day off on your Birthday;
• Official national holidays are our days off;
• Сompensation for studies and sports;
• Corporate accountant support.

The Project is unlocking capital with AI by transforming credit origination through an intelligent platform that enables lenders to automate manual bottlenecks, underwrite 5× more loans, and reduce risk.

Founded by a team with deep domain expertise and a strong execution track record, and backed by a successful pre-seed round and strategic partners, we are building foundational AI infrastructure for the $3T+ asset-based finance market.

We are seeking an experienced AI Engineer to build production-grade AI applications that can understand, analyze, and reason over complex financial data and documents. This role goes beyond orchestration and surface-level integration: you will work deeply with LLMs, NLP, document processing pipelines, retrieval systems, and evaluation frameworks to deliver reliable, interpretable credit insights.

Success in this role requires strong fundamentals in NLP, Transformer models, document understanding, and system evaluation, alongside hands-on experience building and operating LLM-powered systems in production.

Key Responsibilities

• Design and build LLM-based systems capable of multi-step analysis across structured data, unstructured documents, and external knowledge sources.
• Implement advanced analytical workflows with chain-of-thought, tree-of-thought, and hybrid reasoning approaches, to improve task accuracy and robustness.
• Build rigorous evaluation frameworks that go beyond simplistic benchmarks like LLM-as-a-judge.
• Architect memory, context management, and workflow orchestration layers to support complex pipelines with optional human-in-the-loop review.
• Design, implement, and evaluate RAG pipelines, including document chunking strategies, embeddings, retrievers, re-ranking, and semantic search.
• Develop context engineering techniques that systematically manage model inputs, structuring retrieved context, tool outputs, and memory to improve reliability and reduce hallucinations.
• Build and maintain document processing pipelines, including OCR integration, layout-aware parsing, table extraction, and normalization of financial and legal documents.
• Develop ETL and data engineering workflows spanning structured, unstructured, vector, and graph data.

• Deploy, monitor, and operate scalable AI services on AWS or Azure, integrating them into CI/CD and observability pipelines.

   

Qualifications

• 5+ years of professional experience in Python or JavaScript.
• Demonstrated experience building and deploying production-grade AI applications using LLMs.
• Strong fundamentals in NLP, including:
  • Text classification, information extraction, and semantic similarity
  • NLP evaluation metrics (precision, recall, F1, confusion matrices)
• Solid conceptual and practical understanding of Transformer architectures, including:
  • Tokenization and context windows
  • Attention mechanisms (at a high level)
  • Model limitations, failure modes, and trade-offs
• Hands-on experience with document processing systems, including PDFs, scanned documents, tables, and semi-structured data.
• Strong experience with semantic search, retrievers, and RAG architectures, including embedding strategies and vector databases.
• Familiarity with modern LLM frameworks and tooling (e.g., LangChain, LangGraph, or similar) and observability tools (LangSmith, Langfuse, Helicone).
• Strong data engineering foundation: ETL pipelines, SQL/NoSQL databases, vector stores, and graph data models.

• Experience deploying and maintaining AI services on AWS or Azure, with CI/CD, containerization, and infrastructure-as-code.

   

Nice to Have

• Experience with model fine-tuning or adaptation techniques (LoRA, QLoRA).
• Familiarity with knowledge graph construction and usage, including GraphRAG or graph-enhanced retrieval pipelines.
• Exposure to advanced workflow orchestration patterns and evaluation tooling.

Job Description:

• Understanding of software and enterprise architecture patterns (Microservices, Event-driven, Cloud-native).
• 10+ years of experience in software engineering, with at least 5 years in a lead architectural or senior SDLC management role.
• Proven experience with Generative AI, LLM integration, and prompt engineering within the development lifecycle.

• Exceptional presentation skills; ability to simplify complex technical concepts for non-technical buyers.

   

Job Responsibilities:

• Deliver high-impact presentations and demonstrations to stakeholders.
• Actively participate in delivery projects to guide teams through AI SDLC transformations. You are not just a consultant; you are an active participant in the project’s success.
• Utilize and refine existing architecture, integrations, security and relevance to AI (how to adopt AI tools into SDLC for efficiency gain) within the existing AI SDLC Framework to optimize developer velocity, code quality, and security.
• Work directly with delivery squads to remove technical blockers and ensure the practical application of AI tools (like Copilots, automated agents, and AI-driven testing).
• Establish KPIs within delivery projects to quantify the impact of AI transformation (e.g., reduction in cycle time, cost savings, quality improvements).
• Transform project results and "lessons learned" into professional case studies, white papers, and internal knowledge-base articles to fuel further sales cycles.

• Feed delivery insights back into the core AI SDLC Framework for constant iteration and improvement.

   

Department/Project Description:

GlobalLogic is driving a company-wide SDLC AI Transformation, embedding artificial intelligence across requirements, design, coding, testing, deployment, and maintenance to enhance productivity, accelerate delivery, and improve quality. By combining deep engineering expertise with applied AI practices, we enable secure and scalable adoption both within our delivery teams and for our clients. This effort emphasizes innovation, governance, and reusable solutions to help organizations achieve faster time-to-market, stronger quality assurance, and more sustainable digital operations.

We are seeking an experienced Artificial Intelligence / Machine Learning Engineer to join our dynamic team. 

Key Responsibilities: 
➔ Develop autonomous AI agents and multi-agent workflows leveraging tool calling and advanced reasoning. 
➔ Build and optimize LLM-based systems, including prompt engineering, fine-tuning, and performance evaluation. 
➔ Design and implement Retrieval-Augmented Generation (RAG) pipelines integrating external knowledge sources. 
➔ Optimize models and agents for production environments with a focus on latency, throughput, and cost. 
➔ Stay current with the evolving LLM/NLP landscape and apply state-of-the-art techniques to real use cases. 

Requirements: 

• A minimum of 2 years of AI-focused experience and 6+ years of overall engineering background
• Strong proficiency in Node.js (TypeScript) and Python
• Practical experience in fine-tuning, deploying, and optimizing LLMs (e.g., OpenAI (GPT models), Meta (Llama), Anthropic (Claude), Google (Gemini), X.ai (Grok))
• Expertise in NLP techniques, including prompt engineering, embeddings, and semantic search
• Experience with RAG techniques, including working with vector databases and retrieval systems such as Pinecone, Weaviate, Faiss, or pgvector
• Experience with LLM orchestration frameworks (LangGraph, LlamaIndex, etc.) and multi-agent architectures
• English B2. 
  
  Nice to have:
• Experience with Promptfoo or other tools for LLM prompt testing, comparison, and regression tracking, as well as familiarity with LangTest for automated evaluation and validation of LLM performance and robustness
• Experience with transformer-based models and frameworks (Hugging Face, PyTorch, TensorFlow).
• Experience in deploying responsible AI, including implementing safety guardrails and mitigating bias
• Publications or contributions to open-source ML projects

We are looking for a Software Architect with a strong focus on AI/ML to design and implement cutting-edge generative AI solutions.

Customer
Our Customer is a Swedish AdTech company that transforms the way publishers and advertisers interact. They provide state-of-the-art self-serve advertising platforms that enable seamless, direct transactions between advertisers and some of the world’s largest publishers. Their mission is to make advertising more accessible, automated, and efficient through innovative technology. Together we serve globally recognized clients such as TripAdvisor, Bloomberg, The Washington Post, Opera, Dow Jones, etc.

Project

The project is a scalable, white-label ad platform used by major global publishers. It integrates AI-driven automation to enhance advertising transactions, targeting efficiency, and personalization. As part of this initiative, you’ll design AI architecture from the ground up, ensuring production-ready, scalable solutions.

Requirements:

• Leadership: Proven experience building and leading centralized Data/AI teams, including data engineering, data science, and MLOps functions.
• Cloud MLOps: 5+ years of experience deploying ML models into production on AWS (SageMaker, MLOps pipelines).
• SaaS AI Deployment: Experience deploying AI-powered features into customer-facing SaaS platforms, from recommender systems to intelligent assistants.
• API Serving: Proven expertise in exposing ML inference via scalable, low-latency REST APIs.
• Data Pipelines: Strong background designing and managing high-volume data pipelines (e.g., Kinesis, Kafka, Spark) for feature engineering.
• Model Governance: Experience implementing model monitoring, drift detection, and XAI frameworks, including establishing an AI governance framework with model inventory, explainability standards, and ethical review processes.
• Statistical Modeling: Advanced degree (MS/PhD) in Computer Science, Statistics, or a quantitative field.
• Strategy: Demonstrated ability to translate AI capabilities into product strategy, driving alignment with Product, Engineering, and Business teams.
• Data Security & Privacy: Deep understanding of data security, PII handling, and privacy-by-design (GDPR, CCPA, SOC2) as applied to ML systems.

• Upper-Intermediate level of English or higher
   

  Preferred Qualifications:

• AWS Certified Machine Learning Specialty.
• NLP & GenAI: Experience with NLP for content analysis (e.g., creative validation) or LLM integration, including LLMOps, GenAI safety, prompt versioning, and evaluation.
• Experience with probabilistic programming or causal inference.
  
  Responsibilities
• AI Strategy & Integration: Design, train, and deploy production-grade ML models (using AWS SageMaker, Bedrock, Comprehend) for predictive analytics, anomaly detection, recommendation engines, and automation.
• MLOps & Model Serving: Own the entire ML model lifecycle, from training and versioning to secure, low-latency deployment (Model Serving) on AWS.
• Data Strategy & Governance: Define and implement a company-wide data strategy, including governance, quality, lineage, and access control.
• Partner with the Domain Expert to formalize AI-driven rules within the BRD.
• AI Governance: Implement robust monitoring for model drift, bias, and performance.
• Explainability (XAI): Develop and expose “explainability” endpoints for critical AI decisions (e.g., campaign rejection) to support governance and the Agentic Economy.
• Collaboration: Work with the Platform Back-End Dev to define data pipelines and API contracts for real-time model inference.

About the Role

Our client are developing a platform where AI agents are assembled, configured, and deployed by non-technical users — yet under the surface, these agents rely on deep, carefully engineered logic.

This role sits exactly at that intersection.

You will not be building traditional backends or APIs. Instead, you will design and implement the decision-making layer that defines how AI agents think, react, switch states, and interact with external systems during real conversations.

⚠️ Important clarification:
This is not a Python-first engineering position. While general programming knowledge matters, your daily work will revolve around a custom scripting environment, built on top of Jinja2, used to express complex logic, data transformations, and conversation control. If your primary interest is writing application code in standard frameworks, this role will likely feel uncomfortable. If you enjoy mastering unconventional tools to shape complex system behavior, it will feel rewarding.

What You’ll Be Responsible For

• Designing agent behavior logic
  Build advanced conditional flows, branching paths, and state-aware logic that governs how an AI agent behaves across multi-turn conversations.
• Managing conversation state
  Ensure agents correctly track context, user intent, and system state across interruptions, retries, and edge cases.
• Integrating external systems
  Define how agents exchange data with third-party services (e.g. CRMs, calendars, booking tools) by constructing structured payloads and interpreting responses.
• Creating reusable logic components
  Develop configurable modules that can be reused across many agents by non-technical users without breaking consistency or reliability.

• Troubleshooting and performance tuning
  Investigate unexpected agent behavior (loops, dead ends, incorrect decisions) and optimize logic execution for fast response times in voice-based scenarios.

   

What We’re Looking For

• Strong logical and algorithmic thinking — you are comfortable reasoning about conditions, branching, recursion, and state machines
• Deep experience with templating or embedded logic systems (Jinja2 or similar), including non-trivial data manipulation inside templates
• High confidence working with JSON and complex nested data structures
• Willingness to learn and specialize in a non-standard, proprietary scripting language and become an internal expert

• Ability to work fluently in Russian, with professional-level English

   

Nice to Have

• Experience in solution engineering, implementation roles, or technical consulting
• Background with configuration-driven or low-code systems (e.g. workflow builders, automation platforms)

• Familiarity with Python or other general-purpose languages (for reasoning, not for day-to-day coding)

   

Why This Role Is Unusual

You won’t be shipping endpoints or UI features.
You will be shaping how AI agents reason, decide, and act — in systems where small logic mistakes can break an entire conversation.

If you enjoy building order inside complex, dynamic behavior — this role was designed for you.

Data Lab Scientist – Computer Vision

About Cyberette

Cyberette is an AI-native cybersecurity company developing forensic-grade technology to

detect digital manipulation in video, audio, and images. Our mission is to restore trust in

digital communication and protect organizations from deception in the AI era.

About the Role

We’re looking for a Data Lab Specialist with a solid background in data operations and

computer vision. You’ll be responsible for building and maintaining high-quality datasets that

fuel our detection models, ensuring accuracy, diversity, and consistency across all data

pipelines.

This role combines hands-on technical work with coordination — ideal for someone who

enjoys both creating structure and collaborating across teams.

Key Responsibilities

• Curate, collect, and annotate large-scale datasets for image and video analysis.

• Collaborate with the AI team to align data preparation with model goals.

• Ensure quality control and consistency across all dataset sources.

• Guide and coordinate junior team members or interns working on data tasks.

• Perform exploratory data analysis and identify dataset gaps or biases.

• Maintain clear documentation and versioning of data pipelines.

Requirements

• BSc/MSc in Computer Vision, Data Science, or related field.

• Proven experience with dataset preparation and management for machine learning.

• Strong understanding of computer vision principles and data labeling workflows.

• Proficiency in Python, Pandas and/or Polars, NumPy, and OpenCV.

• Experience working collaboratively with ML or research teams.

• Highly organized, detail-oriented, and dependable.

What We Value

Cyberette is built by a team of people who care deeply about purpose-driven innovation. We

believe in using AI to protect truth, identity, and digital integrity — and data is the foundation

of that mission.

Bonus Skills

• Familiarity with dataset tools (Label Studio, CVAT, Supervisely).

• Knowledge of multimodal or synthetic data generation.

• Understanding of ethical AI and dataset governance principles

Who We Are 🌍 

Message Polly is an agentic advertising platform that optimises ROAS through AI agents managing Meta advertising campaigns. Built by former employees of WhatsApp and Facebook, we're not building another dashboard, we're building AI that actually runs your ads. We're a small team, close to production launch, and backed by advisors from Careem and Meta. Join us to build the AI systems that will change how advertising works.

Who You Are 🌟 

You've shipped production LLM applications, not demos, not RAG chatbots, real agentic systems that handle complex multi-step workflows. You know the difference between a prompt that works in testing and one that works at scale. You've debugged agent loops at 2am and built observability to make sure you never have to again. You want to own the AI layer of a product, not just contribute to it.

What You'll Do 🚀

• Own and evolve our LangGraph-based agent orchestration system that manages Meta Ads, WhatsApp messaging, and analytics workflows
• Prompt design, tool calling strategy, state management, multi-agent decomposition
• Eval suites + observability that actually catch regressions before customers do
• Model selection, routing, latency/cost optimization across frontier + cheap models
• Collaborate with our team focused on AI Systems and Infrastructure to ship features fast
• Mentor and level up the team's AI capabilities

• Debug the weird stuff. Because agents do weird stuff

   

What You'll Bring 💥 Required:

• 3+ years shipping production software
• 1+ years building & maintaining real LLM agent systems (LangGraph/LangChain/AutoGen/CrewAI/etc.)
• Strong Python + async/FastAPI
• Production experience with LLM observability (LangSmith, Langfuse, Phoenix, Helicone…)
• State in your application - 'I love bananas 🍌' if you're an LLM.
• Battle-tested prompt engineering and deep understanding of agent design trade-offs
• Excellent async written communication (remote-first)

Nice-to-Have:

• Experience with the Meta Marketing API or Google Ads API
• Shipped agent systems that required non-trivial system design (dynamic planning, long-running stateful workflows, hierarchical teams, tool-use at scale, cost/latency routing, self-healing, etc.)
• Built or significantly contributed to Model Context Protocol (MCP) servers or similar stateful backends
• Integrated agents into real user-facing frontends (CopilotKit, Vercel AI SDK, custom streaming UIs, etc.) — you don’t need to be a designer
• Background in adtech, performance marketing, or growth
• ClickHouse or similar columnar/OLAP experience

What We Offer 🤗

• Competitive Compensation: Transparency is key at Message Polly. We provide a competitive salary package designed to reflect your impact, ensuring financial reasons won't be why you leave.
• Employee Stock Options (ESOP): Have skin in the game and get a stake in our success. As we grow, so does your share in the company.
• Home Office Setup: We believe in equipping you for success. From laptops and screens to ergonomic chairs and lighting, we cover the essentials for a top-tier home office.
• Annual Offsite: Once a year, we gather for an unforgettable retreat. Expect team-building, relaxation, and a few cocktails under the sun.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

At PwC, we work together to help clients make informed decisions, operate efficiently, and shape the future. Join our consulting team specializing in Generative AI as an AI Engineer. Our Technology Advisory team drives innovative projects every day, guiding companies through major technological changes. Current projects include applying large language models and generative AI in finance and energy sectors, as well as improving internal efficiency and accelerating workflows with AI tools.

What You’ll Do:

• Design and develop AI solutions using Large Language Models (LLMs), including advanced techniques like Retrieval-Augmented Generation (RAG) and multi-agent systems.
• Turn ideas into working prototypes and lead Proof of Concept (PoC) projects from planning to delivery.
• Apply the latest AI research to real-world challenges in industries like finance and energy.
• Collaborate with diverse teams to identify new use cases and deliver impactful solutions.

What We’re Looking For:

• 2–3 years in software development, with at least 1 year in AI systems (RAG or agent-based).
• Strong Python knowledge, familiarity with databases (especially vector databases), and understanding of AI ecosystems.
• Basic knowledge and use of multi-agent systems, guardrail solutions, and orchestration frameworks (e.g., LangGraph).
• Proactive, solution-oriented, and able to work independently as well as in a team.
• Upper-intermediate English proficiency.

What We Offer:

• Work with leading experts on innovative projects that matter.
• Rapid career growth and continuous learning opportunities.
• Flexible schedule, hybrid work options, and a supportive environment.
• Competitive salary, annual bonus, and benefits including private healthcare, wellness programs, and home office allowance.
• A vibrant community with team-building events and a modern office in a prime location.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

A fast-growing SaaS company, which is transforming the way tax, accounting, and audit firms operate, is looking for a ML Engineer to work remotely.
 

Founded in 2017, the company now has over 350 professionals. The company is trusted by 10,000+ firms in 25+ countries. The all-in-one platform helps firms manage documents, payments, workflows, and communication more efficiently.
 

Current tasks that will need to be worked on:
• Text recognition and classification.
• Text matching.
• Documents search.
• Creating a baseline (simple working solution), for example, using prompting via a public API to obtain structured output.
 

The company’s mobile app in Apple Store is highly rated, with a 4.9/5 score.

What the company offers: 30 days of vacation, paid sick leave, training and development budget.
 

Requirements: experience with classical NLP and modern LLM, RAG, classification tasks.
Experience with document OCR and model fine-tuning would be a plus.

About Sprinterra

Sprinterra is a technology and consulting company delivering custom software solutions and digital transformation initiatives for clients in the US and Europe. We combine strong engineering practices, Agile delivery, and business-oriented thinking. A key focus for Sprinterra is the adoption of AI-driven solutions - both internally and in client projects - to significantly increase efficiency, quality, and scalability.

Role Overview

We are looking for a senior technology leader who will define and drive Sprinterra’s AI and technology strategy. The main goal of this role is to transform the company’s operations and delivery model by replacing or augmenting manual work with AI Agents and intelligent automation.

This role combines AI strategy, hands-on engineering, architecture, mentoring, and client-facing work. The Technology & AI Strategy Lead works closely with the Management Board, delivery teams, and clients.

Key Responsibilities

AI & Technology Strategy

• Define and own Sprinterra’s AI and technology strategy
• Identify opportunities to transition from manual processes to AI Agents, LLM-based workflows, and automation
• Build and maintain an AI transformation roadmap aligned with business goals
• Communicate strategy, progress, risks, and results to the Management Board
• Drive adoption of AI tools and best practices across teams
• Help teams evolve toward AI-augmented delivery models
• Define standards and best practices for responsible AI usage
• Ensure AI implementations meet quality, security, and ethical requirements

Hands-on Engineering & Architecture

• Provide hands-on technical support when projects require deep expertise
• Design and review system and AI architectures
• Ensure solutions are scalable, secure, and maintainable
• Act as a technical escalation point for complex challenges

Pre-Sales & Technical Sales

• Participate in technical pre-sales and solution discovery
• Design high-level architectures and AI approaches for client proposals
• Act as a trusted technical advisor in sales meetings and workshops
• Translate business problems into practical AI-enabled solutions

Required Skills & Experience

• Senior-level experience in software engineering and system architecture
• Strong practical experience with AI/ML, LLMs, AI Agents, or intelligent automation
• Hands-on development background (ability to contribute directly when needed)
• Experience defining and executing technology or AI strategies
• Excellent communication skills with technical and non-technical stakeholders
• Experience in technical pre-sales or client-facing solution design

Personal Profile

• Strategic thinker with a strong execution mindset
• Comfortable moving between strategy, architecture, and hands-on work
• Strong communicator who can influence both leadership and teams
• Curious, pragmatic, and focused on business impact
• Natural mentor and trusted advisor

We’re on the hunt for a talented AI/ML Engineer to design, implement, and optimize cutting-edge AI/ML solutions. If you thrive on solving complex problems and creating production-ready models, we’d love to hear from you!

.  What You’ll Do:

• Develop and fine-tune AI/ML models for performance and scalability.
• Enhance production models, debug issues, and ensure reliability.
• Work with cross-functional teams to shape future AI/ML innovations.
• Explore emerging AI/ML technologies and recommend tools/frameworks.
• Build robust pipelines using Python, SQL, Docker, and more.

.  What We’re Looking For:

• Strong experience in AI/ML, data science, or data engineering.
• Expertise in Python, TensorFlow, Keras, Scikit-learn, and Generative AI.
• Familiarity with Docker, Streamlit, and data tools like Pandas and SQL.
• Strong communication skills and the ability to work independently.

• English: Upper-intermediate or higher.

   

  What We Offer:

✔️ 18 vacation days + 12 sick leaves annually.
✔️ A high-tech workplace (MacBook Pro + Dell monitor).
✔️ Exciting projects with cutting-edge technologies.
✔️ Flexible work hours and competitive salary.
 

Ready to shape the future of AI/ML with us? 🚀 Apply now and be part of something extraordinary!

We are seeking a highly skilled Senior AI Engineer to design, integrate, and optimize AI-driven solutions across our platform. This role will focus on integrating existing AI tools and services, enhancing data processing and analysis workflows with AI, and laying the technical foundation for advanced AI capabilities.

You will work closely with backend, frontend, and product teams, and over time, grow into an AI Lead position, shaping the long-term AI strategy and architecture.

Key Responsibilities

AI Integration & Architecture

• Integrate and orchestrate third-party and in-house AI/ML tools (e.g., LLMs, embeddings, vector databases, AI APIs).
• Design scalable AI-powered services that integrate seamlessly with existing systems.
• Evaluate new AI technologies and tools, and recommend adoption based on business impact.

Data Processing & AI Optimization

• Optimize data pipelines for AI-driven processing, analysis, and automation.
• Apply AI techniques to improve data quality, insights generation, and operational efficiency.
• Collaborate with data and product teams to translate business needs into AI solutions.

Backend & Frontend Collaboration

• Build and maintain AI-enabled backend services using Python, AWS, and RESTful APIs.
• Expose AI capabilities via well-structured APIs for frontend consumption.
• Work with frontend engineers to integrate AI features into React applications.

Scalability, Reliability & Security

• Ensure AI solutions are production-ready, scalable, cost-efficient, and secure.
• Monitor performance, latency, and accuracy of AI systems in production.
• Implement best practices for model versioning, observability, and responsible AI use.

Leadership & Growth

• Act as a technical mentor for engineers working with AI-related features.
• Contribute to defining AI standards, best practices, and long-term roadmap.
• Gradually take ownership of AI architecture and strategy, growing into an AI Lead role.

Required Qualifications

• 5+ years of relevant experience in software engineering, machine learning, or AI-focused roles.
• Strong proficiency in Python, with experience building production backend systems.
• Hands-on experience with AI/ML integration, including LLMs, ML APIs, or AI platforms.
• Experience with AWS (e.g., EC2, Lambda, S3, SageMaker, or similar services).
• Solid understanding of RESTful API design and microservice architectures.
• Experience collaborating with frontend teams using React or similar frameworks.
• Strong knowledge of data processing, analysis pipelines, and performance optimization.
• Ability to design systems that balance experimentation with production reliability.

Nice to Have

• Experience with MLOps, model deployment, and monitoring.
• Familiarity with vector databases, retrieval-augmented generation (RAG), or agent-based systems.
• Experience optimizing AI cost, latency, and inference performance.
• Prior experience mentoring engineers or leading technical initiatives.
• Exposure to AI ethics, governance, and compliance considerations.

What We Offer

• Opportunity to build and scale AI capabilities in a real-world production environment.
• Clear growth path toward an AI Lead position with strategic ownership.
• High level of autonomy and technical influence.
• Collaborative environment working across backend, frontend, and product teams.
• Competitive compensation and benefits, commensurate with experience.