Job Description, Responsibilities & Requirements
About the Position
Forward Deployed Engineer (Chief Role)
Join EPAM Systems as a Forward Deployed Engineer (Chief Role) in Romania, focusing on building AI-native solutions and agentic systems. This role is remote and requires you to work closely with SMEs and end-users to understand where the real value lies, and you design the feedback loops.
Responsibilities
- Design, build, and ship AI-native systems E2E - agents, workflows, RAG, and the harness: custom tool calling, sandboxing, context engineering and sub-agents, caching, compaction
- Build the evaluation pipelines and use them to prove the system is genuinely useful
- Design for failure in the agent loop: retries, model fallbacks, cost limits, and human-in-the-loop on consequential actions
- Capture domain expertise and repeatable workflows - so what works on one engagement carries to the next
- Engage early, to help shape the use case and check technical feasibility
- Write production-grade Python: integrations, APIs, data access, deployment
- Work directly with SMEs and end-users - interviews, UAT, observing the real workflow - and validate that the system fits how people actually work
Requirements
- 7+ years of engineering experience, with a strong recent track record building production AI / LLM applications (not prototypes or research only)
- Strong agent-design judgment - task-harness fit, matching the harness to the context, failures, and policies of the actual task rather than calling a model in a loop
- The ability to operate close to the client: lead discovery and feasibility conversations, work directly with SMEs and end-users, and explain technical trade-offs to both technical and non-technical audiences
- Hands-on experience with agentic frameworks (LangChain, LangGraph, Semantic Kernel, or similar) and major LLM providers (OpenAI, Anthropic, Google Gemini)
- Expert-level Python and solid software engineering fundamentals
- Strong RAG and retrieval skills: vector databases, embeddings, hybrid search, re-ranking, chunking, and context management
- Proven experience evaluating generative AI quality - LLM-based evaluation, heuristics, custom eval frameworks - and using observability/tracing tools (LangSmith, Arize Phoenix, Langfuse, or similar)
- Production deployment experience on at least one major cloud (AWS, Azure, or GCP) with containerization, CI/CD
- Sound judgment under ambiguity - scoping, sequencing, and making the call on speed vs. quality vs. scope
- English at C1 level
Nice to Have
- Experience designing experiments, A/B testing, and iterating on AI products against real user behavior and business metrics
- Background in NLP, Data Science, or applied ML, with experience moving models into production
- Familiarity with MCP, A2A, Agent Skills, and emerging agent standards
- Experience with enterprise AI platforms (AWS Bedrock AgentCore, Databricks Genie, Microsoft Foundry, Gemini Enterprise)
- Exposure to AI governance, security, and compliance (guardrails, prompt-injection prevention)
- Prior client-facing or pre-sales exposure in a consulting or services context
We Offer
- Opportunity to work with cutting-edge AI technologies
- Remote work from Romania
- Be part of a leading company in AI-native solutions
About the Company
EPAM builds AI-native solutions for our clients - products where LLM and its harness are the core of the value. We are committed to delivering innovative and impactful solutions to our clients.