Principal Forward Deployed Engineer (relocation to Lithuania)

We are looking for a Principal Forward Deployed Engineer to join our team with eventual relocation to Lithuania. EPAM is renowned for delivering cutting-edge technological solutions to transform businesses worldwide.

We are building AI-native solutions for our clients - products where LLM and its harness are the core of the value. This is a builder's role: you and your team are responsible for building agentic systems, writing the production code, and standing up the evals and observability. You will work closely with SMEs and end-users to understand where the real value lies, and you design the feedback loops.

The deadline for submission is 01.12.2026.

Design, build and ship end-to-end AI-native systems including agents, workflows, RAG and integration harnesses Write production-grade Python code for integrations, APIs, data access and deployment Work directly with subject matter experts and end-users through interviews, user acceptance testing and workflow observations Engage early in projects to shape use cases and check technical feasibility Build evaluation pipelines and use them to prove system utility Design for failure in the agent loop by implementing retries, model fallbacks, cost limits and human-in-the-loop actions Capture domain expertise and repeatable workflows to ensure success across engagements. Troubleshoot and resolve technical challenges in collaboration with the broader team Ensure adherence to engineering excellence standards including test-driven development and continuous integration practices 7+ years of software engineering experience with a strong track record of building production AI and LLM applications Expert-level Python skills and solid software engineering fundamentals Hands-on experience with agentic frameworks such as LangChain, LangGraph or Semantic Kernel and major LLM providers Strong RAG and retrieval skills including vector databases, embeddings, hybrid search and context management Production deployment experience on major cloud platforms like AWS, Azure or GCP with containerization and CI/CD Proven experience evaluating generative AI quality using custom evaluation frameworks and observability tools Proven capability to work closely with clients, lead discovery conversations and explain technical trade-offs to diverse audiences Strong agent-design judgment and sound engineering judgment under ambiguity to balance speed, quality and scope C1 level English language proficiency An academic degree in Computer Science, Software Engineering or a related field Experience designing experiments, A/B testing and iterating on AI products against real user behavior Strong background in NLP, Data Science or applied machine learning with experience moving models into production Familiarity with Model Context Protocol (MCP), Agent-to-Agent (A2A), Agent Skills and emerging agent standards Experience with enterprise AI platforms such as AWS Bedrock AgentCore, Databricks Genie or Microsoft Foundry Exposure to AI governance, security and compliance including guardrails and prompt-injection prevention