Lead Python AI Engineer: Agents & Tooling Architect

EPAM Systems, Inc.; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling courses

LinkedIn Learning access

Job summary

EPAM Systems, Inc. seeks a Lead AI Engineer to design production-grade AI agents and data-integrated tool APIs in a cloud-native Python environment. You will shape agent architecture, ensure observability, and collaborate with distributed stakeholders to ship high-quality outcomes.

Responsibilities include building AI agents, tool interfaces, and read-only data access, plus developing FastAPI services and SQL queries while enforcing best practices and tests across the codebase.

Qualifications

• 5+ years of production Python development.
• 2+ years building LLM integrations or AI agents.
• Lead-level technical leadership for design and code quality.
• Strong async programming with Python 3.11+.
• Experience with FastAPI and backend microservices.

Responsibilities

• Design production-grade AI agent architectures and tool interfaces.
• Build scoped AI agents with tool-calling and robust orchestration.
• Develop read-only Model Context Protocol servers exposing enterprise data.
• Create FastAPI services and asynchronous task handlers for low-risk actions.
• Write and optimize SQL for cost datasets with partitioning constraints.
• Establish tests, observability, tracing, and distributed logging; enforce monorepo practices.

Tools

Python

AsyncIO

FastAPI

SQL

Docker

Google Cloud

BigQuery

LangChain

LLM integrations

Terraform

Job description

EPAM Systems, Inc. seeks a Lead AI Engineer to design production-grade AI agents and data-integrated tool APIs in a cloud-native Python environment. You will shape agent architecture, ensure observability, and collaborate with distributed stakeholders to ship high-quality outcomes.

Responsibilities include building AI agents, tool interfaces, and read-only data access, plus developing FastAPI services and SQL queries while enforcing best practices and tests across the codebase.