Forward Deployed Engineer/Chief Role

EPAM Systems; Turkey; On-site; TRY 4,375,000 - 5,834,000; Full time

Benefits offered by this job

Private health insurance

English courses and learning stipend

Mentoring programs

Job summary

EPAM Systems is seeking a senior engineer to design and ship AI-native systems end-to-end, including agents, workflows, and RAG components. You will work with SMEs and end-users to validate use cases, build evaluation pipelines, and ensure production-grade quality with robust observability.

You will prototype and ship in Python, deploy to cloud environments, and apply agentic frameworks to real-world tasks while maintaining strong client-facing communication and governance.

Qualifications

• 7+ years of engineering experience with production AI/LLM applications
• Strong agent-design judgment prioritizing context, failures and policies
• Ability to lead discovery with SMEs and end-users and explain trade-offs
• Hands-on experience with agentic frameworks and major LLM providers
• Expert-level Python and solid software fundamentals
• Strong RAG and retrieval skills: vector databases, embeddings, hybrid search
• Experience deploying to at least one major cloud with containers and CI/CD
• Strong judgment under ambiguity and English at C1 level

Responsibilities

• Design, build and ship AI-native systems end-to-end — agents, workflows, RAG and the harness
• Build evaluation pipelines to prove usefulness of the system
• Design for failure in the agent loop with retries, fallbacks and human-in-the-loop
• Capture domain workflows to enable reuse across engagements
• Engage early with clients to shape use cases and assess feasibility
• Write production-grade Python for integrations, APIs and deployment
• Collaborate with SMEs and end-users through interviews and UAT to validate fit

Skills

Python

Agent design

LangChain

LangGraph

Semantic Kernel

LLM apps

CI/CD

Cloud deployment

English (C1)

Education

Bachelor's degree in CS/Engineering

Tools

LangSmith

Arize Phoenix

Langfuse

AWS

Azure

GCP

Job description

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)

We offer

• 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.

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.