Senior AI Platform Engineer - RAG & LLM Systems

EPAM Systems, Inc.; Turkey; On-site; TRY 2,457,000 - 4,423,000; Full time

Benefits offered by this job

Learning & Development

Mentoring programs

Private health insurance

English courses

Career growth

Job summary

EPAM Systems, Inc. seeks a Senior AI Engineer to join an enterprise AI platform engineering initiative.

You will design and implement core AI agents on a Databricks-native platform, ensuring production-ready deployment with robust guardrails and evaluation-driven quality gates. You will collaborate across data, QA, and business teams to translate requirements into scalable, end-to-end AI solutions, delivering capabilities across GCP and Azure environments.

Qualifications

• 3+ years of experience building LLM-based applications in Python.
• Hands-on with RAG pipelines, covering retrieval, chunking, embedding, reranking, and generation.
• Proficiency in prompt engineering, including system prompt design, few-shot patterns, and output structuring.
• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or equivalent.
• Familiarity with LLM evaluation techniques, including LLM-as-judge, RAG faithfulness metrics, and RAGAS or equivalent.
• Expertise in Databricks and MLflow, including experiment tracking and model serving awareness.
• Knowledge of MCP (Model Context Protocol) or equivalent tool-use / function-calling patterns.
• Experience with vector stores such as Chroma, Pinecone, or Databricks Vector Search, or equivalent.
• Skills in REST API integration and OAuth authentication flows.

Responsibilities

• Participate in use case deep-dive sessions and translate requirements into specifications.
• Design and implement the RAG pipeline including document retrieval, embedding, and reranking.
• Integrate agents with platform MCP servers and LLM Gateway for routing.
• Implement prompt engineering practices and iterate based on evaluation results.
• Wire guardrails and domain boundaries for reference agents.
• Run evaluation cycles using the platform Evaluation Framework and improve quality gates.
• Collaborate with Data Engineer on data schema and retrieval interface design; with QA on test coverage.
• Support UAT with business stakeholders and prepare agents for production deployment.

Skills

Python

LLM-based apps

RAG pipelines

Prompt engineering

LangChain

LlamaIndex

Databricks

MLflow

MCP

Vector stores

REST API

OAuth

English (B2+)

Tools

Databricks

MLflow

LangChain

LlamaIndex

Chroma

Pinecone

Databricks Vector Search

Job description

EPAM Systems, Inc. seeks a Senior AI Engineer to join an enterprise AI platform engineering initiative.

You will design and implement core AI agents on a Databricks-native platform, ensuring production-ready deployment with robust guardrails and evaluation-driven quality gates. You will collaborate across data, QA, and business teams to translate requirements into scalable, end-to-end AI solutions, delivering capabilities across GCP and Azure environments.