Chief Forward Deployed Engineer

EPAM Systems; Poland; Hybrid; PLN 260,000 - 380,000; Full time

Benefits offered by this job

Hybrid work model

Opportunity to work abroad up to 60,00

Relocation opportunities

Health insurance

Employee Stock Purchase Plan (15% 할인)

Job summary

EPAM Systems is seeking a Chief Forward Deployed Engineer to lead the design, build and deployment of AI-native systems, including agents, workflows, RAG, and the harness. You will write production-grade Python, build evaluation pipelines, and ensure observability and reliability in collaboration with SMEs and end-users.

You will apply strong agent-design judgment, work closely with clients, and leverage frameworks like LangChain and Semantic Kernel, delivering production-scale, cloud-deployed

Qualifications

• 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

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

Skills

Engineering experience

Python

Agent design

LLM applications

Cloud deployment

Observability & tracing

SME collaboration

English (C1)

CI/CD

Containerization

Tools

LangChain

LangGraph

Semantic Kernel

OpenAI

Anthropic

Azure

AWS

GCP

LangSmith

Arize Phoenix

Langfuse

Job description

We are looking for a Chief Forward Deployed Engineer to build AI-native solutions 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 will 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

• We gather like-minded people:
  • Top tech minds driving innovation in AI, cloud and digital platform modernization
  • Supportive team and agile, startup-like culture
  • Hybrid by design mode and opportunity to work remotely within Poland
  • Chance to work abroad for up to 60 days annually
  • Business-driven relocation opportunities
• We provide growth opportunities:
  • Career development programs
  • Thought leadership, mentoring, soft skills and well-being programs
  • Certification (Anthropic, Gemini, GCP, Azure, AWS)
  • English classes
• We cover it all:
  • Stable pay
  • Participation in the Employee Stock Purchase Plan with a 15% discount
  • Benefits package (health insurance, multisport, shopping vouchers)
  • Referral bonuses up to $2,000
  • Offices featuring entertainment and relaxation zones, table tennis and football, free snacks, coffee and more
  • Corporate, social and well-being events
• Please, note:
  • Benefits listed above are available to employees only
  • We are open for working with Contractors. Terms of B2B cooperation agreements are agreed individually
  • We will reach out to selected candidates exclusively

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.