Lead AI Engineer

We are seeking a Lead AI Engineer to build a central GenAI Platform, empowering hundreds of product teams across the organization with scalable capabilities for rapid development, validation, and deployment of AI agents. In this role, you will drive the development of impactful AI agents, ensuring faster delivery and greater impact across multiple domains. You'll design and ship full-stack systems, shape platform capabilities, and lead by example through engineering craftsmanship. This position is based in Lithuania, with relocation support available from EPAM. Learn more about the benefits EPAM Lithuania provides in the description below. Responsibilities Design and implement full-stack applications, AI agents and platform components that enable rapid GenAI agent development, validation and deployment Build developer tooling, CI/CD and observability for safe, fast iteration (evals, canaries, rollout/rollback, cost and quality telemetry) Apply secure SDLC and privacy-by-design practices (threat modeling, least privilege) Collaborate with product, UX and domain experts to deliver customer-focused solutions with measurable outcomes Apply current LLM patterns (e.g., RAG, retrieval, routing, tool-use, evaluation) to deliver measurable customer value-faster, more reliable AI systems; reduced time-to-decision; improved trust/safety metrics; and lower cost per query Lead by example through writing high-quality, maintainable code Requirements 5+ years of professional software engineering experience with Python, TypeScript and AWS/Azure/Google Cloud Platform 1+ years of leadership experience Strong full-stack development skills in backend (Python, FastAPI, TypeScript) and frontend (TypeScript, Streamlit, Gradio) Proficiency in cloud platforms, CI/CD and Infrastructure as Code Expertise in at least one of: AI Agent development and evaluation (LLM platforms, APIs and frameworks such as LangChain), advanced AI integration patterns (e.g., RAG, Agents), or Site Reliability Engineering, quality engineering and secure SDLC Proven track record delivering secure, scalable, cloud-native and AI-driven systems Background in deploying and evaluating AI solutions at scale Familiarity with vector databases (e.g., Qdrant, FAISS, Chroma) Capability to assess generative AI quality using retrieval, classification and LLM-based evaluation metrics Strong problem-solving, ownership and cross-functional communication skills English proficiency at B2 level or higher Nice to have Background in A/B testing, experiment design and model iteration Knowledge of retrieval systems and ranking algorithms Familiarity with emerging AI protocols (MCP, A2A, ACP) Expertise in cloud/on-prem AI platforms and enterprise AI solutions Skills in observability and monitoring tools Technologies Python, TypeScript, PyTorch, Hugging Face, LangChain Vector databases (Qdrant, FAISS, Chroma) LLM APIs (Azure OpenAI, AWS Bedrock)