Senior AI Engineer - RAG & Agentic LLM Architect

EPAM Systems, Inc.; Turkey; On-site; TRY 2,943,000 - 5,885,000; Full time

Job summary

EPAM Systems, Inc. is seeking a Senior AI Engineer to design and deliver LLM-powered applications and agentic systems that solve real problems for users and teams.

You will work across the full applied-AI stack—from RAG pipelines to multi-step agents that reason, use tools, and automate end-to-end workflows. You will collaborate with product, data, and platform teams to turn ambiguous problems into shipped AI features, implementing guardrails and observability to maintain quality, latency, and

Qualifications

• 3+ years in software or ML engineering with hands-on LLM builds.
• Proven end-to-end applied-AI system delivery experience.
• Advanced Python proficiency.
• Hands-on with RAG systems and vector databases.
• Expertise in LLM APIs and orchestration frameworks.
• Experience designing agentic architectures and tool use.
• Ability to automate workflows with agentic AI tooling.
• Knowledge of prompt engineering and structured/JSON outputs.
• Strong English communication (B2+).

Responsibilities

• Design and deliver production LLM applications from concept to scale.
• Build and implement RAG pipelines: embeddings, vector search, grounding.
• Develop agentic architectures: multi-step reasoning and tool calling.
• Integrate LLMs with internal data, APIs, and connectors.
• Define prompts, evaluation harnesses; manage quality, latency, cost.
• Implement guardrails and observability (tracing, evals, drift monitoring).
• Collaborate with product, data, and platform teams to ship AI features.
• Share knowledge and participate in design reviews.

Skills

Python

RAG pipelines

Embeddings

Vector databases

LLM APIs

LangChain

Agent orchestration

Tool use & function calling

Prompt engineering

Quality/latency/cost trade-offs

Tools

Pinecone

Qdrant

Milvus

pgvector

Job description

EPAM Systems, Inc. is seeking a Senior AI Engineer to design and deliver LLM-powered applications and agentic systems that solve real problems for users and teams.

You will work across the full applied-AI stack—from RAG pipelines to multi-step agents that reason, use tools, and automate end-to-end workflows. You will collaborate with product, data, and platform teams to turn ambiguous problems into shipped AI features, implementing guardrails and observability to maintain quality, latency, and