AI Engineer (LLM) at EPAM

Role overview

Join EPAM Vietnam as an AI Engineer (LLM) and help shape the future of AI-powered retail decision-making. You will design agent workflows, prompt and retrieval logic and production-ready services that turn data into grounded, traceable recommendations for business users. Working with cutting-edge AI technologies, structured business data and real-world retail challenges, you will play a key role in creating impactful, scalable and user-centric GenAI experiences that deliver measurable business value.

Responsibilities

• Translate category management needs into LLM and GenAI use cases and workflows.
• Design agent orchestration including prompt strategy, retrieval, tool calling and state handling.
• Build back-end services and APIs for LLM applications using FastAPI and Python.
• Integrate LLM providers such as Azure OpenAI and OpenAI with streaming, retries and cost controls.
• Build retrieval patterns with chunking, metadata, citations and relevance tuning.
• Define evaluation approaches for relevance, grounding, safety, latency and cost.
• Improve quality through testing, observability, feedback loops and iteration.
• Partner with product, data, engineering and business stakeholders to ship usable features.

Qualifications

• Proven experience in Python back-end development, async patterns and FastAPI.
• Hands-on work integrating Large Language Model (LLM) APIs such as Azure OpenAI or OpenAI.
• Understanding of LangChain or LangGraph for agent orchestration and tool workflows.
• Expertise designing tool or function calling, from schemas to retries, confirmation flows and payload contracts.
• Experience implementing Retrieval-Augmented Generation (RAG) with traceable sources and robust evaluation.
• Able to manage agent state through checkpointing, resumability and session handling.
• Understanding of secure design for LLM applications, from secrets management to access control and prompt leakage prevention.
• Clear communication with technical and business partners.

Technology in this role

• AI: Join EPAM Vietnam as an AI Engineer (LLM) and help shape the future of AI-powered retail .
• Python: Build back-end services and APIs for LLM applications using FastAPI and .
• FastAPI: Build back-end services and APIs for LLM applications using FastAPI and .
• LLM: Join EPAM Vietnam as an AI Engineer (LLM) and help shape the future of AI-powered retail .
• RAG: Experience implementing Retrieval-Augmented Generation (RAG) with traceable sources and robust .
• LangChain: Understanding of LangChain or LangGraph for agent orchestration and tool .
• Azure: Integrate LLM providers such as Azure OpenAI and OpenAI with streaming, retries and cost .

Role-specific candidate guide

Preparation notes based on the employer’s stated responsibilities and qualifications.

Understanding the scope. This AI Engineer (LLM) position at EPAM is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “Join EPAM Vietnam as an AI Engineer (LLM) and help shape the future of AI-powered retail decision-making. You will design agent workflows, prompt and retrieval logic and production-ready services that turn data into…” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the AI and data area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.

What the responsibilities signal. The posting specifically names “Translate category management needs into LLM and GenAI use cases and workflows.”; “Design agent orchestration including prompt strategy, retrieval, tool calling and state handling.”; “Build back-end services and APIs for LLM applications using FastAPI and Python.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved from the initial need to implementation, review, release or operational follow-through, where those stages apply. If the work involved other teams or users, distinguish your decisions from the group’s contribution. Avoid presenting a technology keyword as proof by itself: connect it to the problem you solved, the scale or complexity involved, and what changed after your work. The source may contain additional duties; review it directly before preparing your application.

How to read the requirements. The listed qualifications include “Proven experience in Python back-end development, async patterns and FastAPI.”; “Hands-on work integrating Large Language Model (LLM) APIs such as Azure OpenAI or OpenAI.”; “Understanding of LangChain or LangGraph for agent orchestration and tool workflows.”. Mark each requirement as demonstrated, adjacent experience or a genuine gap, then use a concise example for the first two categories. A strong example explains what you personally owned, how you made trade-offs, how you validated the result and what you learned. If the posting specifies years of experience, language ability, certifications, location or eligibility, address those facts plainly in your CV or application rather than relying on the employer to infer them. Do not claim a qualification from exposure alone. For a requirement you do not meet, describe relevant transferable experience accurately and ask the recruiter whether it is mandatory.

Technology and working evidence. The technology terms associated.

About EPAM

EPAM provides software development and digital platform engineering services for international clients.

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