Forward Deployed Engineer/Chief Role

EPAM SYSTEMS TURKEY YAZILIM GELİŞTİRME LİMİTED ŞİRKETİ

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.

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 through interviews, UAT and 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.
• Capability 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) 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).
• Production deployment experience on at least one major cloud (AWS, Azure, 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 and Agent Skills, and emerging agent standards.
• Experience with enterprise AI platforms (AWS Bedrock AgentCore, Databricks Genie, Microsoft Foundry).
• Exposure to AI governance, security and compliance (guardrails, prompt-injection prevention).

Yan Haklar

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT
• Diversity of tasks and projects
• Assessment center for objective review of competency level
• Personal development plan
• Mentoring programs and leadership development
• Certification and professional development support
• Access to learning platforms including more than 2,500 internal courses
• English courses taught by certified teachers

CORPORATE BENEFITS

• Extra leave days
• Referral bonuses

COMPENSATION PACKAGE

• Competitive compensation paid in USD
• Regular salary and performance reviews

MEDICAL & HEALTHCARE

• Private health insurance
• Well-being events

WORKING ENVIRONMENT

• Recreation areas and kitchens
• Tea, coffee and snacks
• Sports equipment and game consoles
• IT Equipment
• Microsoft’s Software Assurance Home Use Program (HUP)

Please note that our Talent Attraction Team reviews applications and CVs submitted in English.

Beceriler: AI Solution Engineering