Principal Forward Deployed Engineer (relocation to Latvia)
We are looking for a Principal Forward Deployed Engineer to join our team with eventual relocation to Latvia. 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.
Responsibilities
- 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
Requirements
- 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
Nice to have
- 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
