Senior AI Engineer: RAG & Agentic LLM Apps

EPAM Systems; Turkey; On-site; TRY 5,900,000 - 8,850,000; Full time

Benefits offered by this job

Private health insurance

Continuous upskilling

Internal courses access

Career development programs

Job summary

EPAM Systems, Inc. is seeking a Senior AI Engineer to design and deliver LLM-powered applications and agentic systems that solve real user problems. You will span the full applied-AI stack from RAG pipelines to multi-step agents that reason and automate workflows.

Collaborate with product and data teams to productionize AI features, optimize performance and cost, and implement safety guardrails. Strong Python, LLM APIs, and vector database experience are required.

Qualifications

• 3+ years in software or ML engineering, including hands-on experience building and shipping applications with LLMs.
• Proven experience delivering applied-AI systems end to end.
• Advanced proficiency in Python.
• Hands-on background in building RAG systems — embeddings, retrieval, and reranking with vector databases.

Responsibilities

• Design and deliver production LLM applications — chat, copilots, assistants, and autonomous workflows — from concept to scale.
• Build and implement RAG pipelines: chunking, embeddings, vector search, reranking, and grounding to reduce hallucination and improve relevance.
• Develop agentic architectures: multi-step reasoning, tool/function calling, planning, memory, and multi-agent orchestration.
• Contribute to automation of business and engineering workflows using agentic AI and workflow automation tooling.
• Define prompt and context strategies; build evaluation harnesses and uphold quality, latency, and cost standards.
• Integrate LLMs with internal data, APIs, and tools via connectors, function calling, and structured outputs.

Skills

Python

LLMs

RAG systems

Vector databases

LangChain

Agent orchestration

JSON outputs

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 user problems. You will span the full applied-AI stack from RAG pipelines to multi-step agents that reason and automate workflows.

Collaborate with product and data teams to productionize AI features, optimize performance and cost, and implement safety guardrails. Strong Python, LLM APIs, and vector database experience are required.