[Hiring] Lead Python AI Agent Engineer @EPAM Systems

Role Description

We are looking for a hands-on Lead Full-Stack AI Agent Engineer to drive the technical development of an enterprise-grade multi-agent AI platform and a suite of analytical AI agents for the Finance & Accounting domain. In this role, you will lead the engineering of a production-ready agentic platform built on Microsoft Azure and Microsoft Foundry, combining LLM-based reasoning, deterministic business logic, and statistical anomaly detection to deliver reliable, secure, and scalable AI-driven analytical solutions.

This is not a traditional chatbot or document-based RAG development role. You will be responsible for building the core agentic infrastructure, including:

• Orchestration
• Shared memory
• Model routing
• Security mechanisms
• Reusable agent architecture

You will combine hands-on engineering with technical leadership, setting engineering standards, guiding developers, and ensuring production readiness.

Responsibilities

• Technical Leadership: Lead a dedicated AI engineering team, provide hands-on technical guidance, conduct code reviews, establish engineering standards, and develop reusable agent templates and architectural patterns.
• Multi-Agent Platform Development: Design and implement the core agentic architecture, including the Master Orchestrator, Agent Registry, multi-LLM routing (Claude and Azure OpenAI), and multi-level caching mechanisms (Redis and prompt caching).
• Context and Memory Management: Develop shared context and memory services to manage domain glossaries, business rules, analytical thresholds, and persistent user feedback. Implement mechanisms that allow agents to retain user confirmations, dismissals, and false-positive suppression rules.
• AI-Powered Analytical Workflows: Build specialized analytical and control agents that work with structured financial and ERP data. Combine deterministic business rules, Python-based statistical anomaly detection, and LLM-generated explanations supported by data references and citations.
• Enterprise Security and Governance: Implement secure identity propagation using Microsoft Entra ID and On-Behalf-Of (OBO) flows, Role-Based Access Control (RBAC), and row-level security. Ensure data freshness, traceability, and reliable citation mechanisms to prevent unsupported AI-generated insights and unauthorized data access.
• Observability and Production Support: Implement operational and business KPI monitoring, build telemetry dashboards, lead production releases, and support hypercare activities and knowledge transfer to the client's IT team.

Qualifications

• Strong Python Backend Engineering: Advanced experience with Python 3.11+, asyncio, FastAPI, Pydantic v2, pytest, strict typing, and clean, modular software architecture.
• Production-Grade Agentic AI Development: Hands-on experience designing and implementing multi-agent AI systems using Microsoft Foundry (Azure AI Agent Service), Semantic Kernel, LangGraph, or AutoGen. Understanding of orchestrator–subagent patterns, MCP (Model Context Protocol), and structured tool calling.
• State Management and Caching: Production experience with Redis for session management and semantic caching, as well as PostgreSQL, Cosmos DB, or similar databases for persistent agent memory, audit logs, and user feedback.
• Azure Security and Identity Management: Practical experience with Microsoft Entra ID (Azure AD), OAuth 2.0 On-Behalf-Of (OBO) flows, RBAC, and Azure Key Vault.
• LLMOps and Observability: Experience with OpenTelemetry, Azure Application Insights, Langfuse or Microsoft Foundry tracing, prompt caching, and LLM token usage and cost optimization.

Nice to have

• Experience developing AI-driven solutions for Finance, Accounting, Audit, or ERP analytics.
• Experience integrating AI applications with Microsoft Fabric or enterprise SQL data warehouses.
• Experience designing enterprise-grade AI platforms with a focus on scalability, security, governance, and performance.