Build production-grade AI infrastructure with Python and FastAPI at EPAM Systems, supporting enterprise knowledge systems and reliable retrieval. Work across backend services and observability.
As a Python AI Engineer, you will evolve a Confluence-focused RAG chatbot into a broader agentic knowledge system. You will use Pydantic, SQLAlchemy async, asyncpg, and modern retrieval pipelines. Your work will support ingestion, evaluation, agent runtime capabilities, and shared conversational platform primitives.
Key Responsibilities: Architect backend services with Python 3.11 and FastAPI
Design retrieval trade-offs involving quality, latency, cost, and safety
Build agent memory boundaries, tool sandboxing, permissions, and budget controls
Improve grounding, failure analysis, and citation enforcement




Create observability using OpenTelemetry, Prometheus/Grafana, Docker, Helm, and GitHub Actions
Requirements: Strong hands-on Python experience in infrastructure-heavy environments
Experience building CLI tools with Python, Golang, or Rust
Hands-on LangGraph, LangChain, pgvector, and retrieval pipeline experience
Experience designing LLM evaluation frameworks and regression detection
Solid Docker, Helm, GitHub Actions, and Kubernetes workflow experience
Apply Python, retrieval, agent infrastructure, and observability expertise to dependable enterprise AI systems at EPAM Systems.

#J-18808-Ljbffr

📌 Python AI Infrastructure Engineer (Manitoba)
🏢 EPAM Systems
📍 Manitoba