[Hiring] AI Engineering Manager @EPAM Systems

Role Description

We are looking for an AI Engineering Manager to architect and deliver a greenfield multi-agent AI platform focused on proactive FinOps outcomes in a multi-cloud environment. You will guide agent orchestration, governance, security controls, and service integrations while mentoring engineers.

• Design the end-to-end architecture for a multi-agent AI platform with specialized agents and clear execution boundaries
• Lead the implementation of agent orchestration, inter-agent dependencies, tool definitions, and agent-to-service communication
• Enforce centralized LLM routing and governance with cost controls, monitoring, and operating limits
• Define compliance guardrails with segregation-of-duties workflows and auditable approval paths for financial-adjacent actions
• Architect the action-routing layer for direct API execution, event-driven workflows, and ticket-based fallbacks
• Establish coding, testing, formatting, and API/schema standards and drive rigorous code reviews
• Implement Zero Trust security controls, identity and access patterns, and immutable audit logging across services
• Guide prompt and tool lifecycle practices to improve reliability, structured outputs, and safe execution
• Coordinate integration with platform services and backend APIs to ensure scalable enterprise adoption
• Mentor engineers through technical design, reviews, and delivery planning
• Validate error handling and contract compliance using standard specifications for APIs and MCP interactions

Qualifications

• 8+ years of software engineering experience and 3+ years in technical leadership for LLM or agent-based platforms
• Proven leadership skills to mentor engineers and drive code reviews and engineering standards
• Hands-on project experience delivering greenfield, enterprise-grade AI services in cloud environments
• Advanced Python 3.11+ skills with FastAPI and agent/service integration patterns
• Strong solution architecture skills for multi-agent orchestration and service-to-agent communication
• Solid AI solution engineering skills including prompt lifecycle, tool definitions, and structured outputs
• Google Cloud Platform experience including Vertex AI and secure identity patterns for workloads
• FastMCP experience building agent toolchains and MCP-based integrations
• Strong security and governance knowledge including Zero Trust, RBAC, and immutable audit logging
• Clear communication skills to align technical decisions across engineering and stakeholder groups
• Upper-Intermediate English proficiency (B2)
• Ability to coach and influence teams beyond hands-on implementation

Nice to have

• Docker
• Google Kubernetes Engine
• Google Cloud BigQuery
• LangChain
• Technical Leadership