Lead AI Engineer — TCO Agent Platform

EPAM Systems

  • Anywhere, CA
  • 2 days ago

    Highlights

    You will drive core architectural execution, ensure strict adherence to SOX-adjacent financial controls, enforce Zero Trust security models via Model Armor and LiteLLM, and guide the engineering team through building high-scale, autonomous enterprise AI services. • Experience: 8+ years of software engineering experience with 3+ years in a technical leadership capacity building multi-agent AI systems, FinOps tools, or LLM-powered platforms.

    Numbers & Facts

    LocationAnywhere, CA

    Description

    As the Lead AI Engineer for our next-generation TCO Agent Platform, you will serve as the technical lead and multi-agent system architect for a greenfield, proactive FinOps AI platform. You will oversee the development, orchestration, and governance of an ecosystem comprising 8 specialized AI agents (e.g., Commitment Optimization, Financial Operations, Resource Optimization, Anomaly Detection) running within a multi-cloud GCP/AWS environment.

    You will drive core architectural execution, ensure strict adherence to SOX-adjacent financial controls, enforce Zero Trust security models via Model Armor and LiteLLM, and guide the engineering team through building high-scale, autonomous enterprise AI services.

    Reporting directly to the Technical Product Manager, you will collaborate closely with Solution, Platform, and Enterprise Architects. You will also have a Senior Software Engineer under your direct subordination to collaborate with on solution implementation.

    Responsibilities

    • Multi-Agent Architecture & Orchestration: Lead the design and implementation of 8 specialized agents using Python, FastMCP, and GCP Workload Identity. Oversee inter-agent dependencies, prompt engineering lifecycle, tool definitions, and agent-to-service communication

    • LLM Governance & Tokenomics: Enforce centralized LLM routing via LiteLLM Gateway and Vertex AI Model Garden (Claude, Gemini). Implement agent self-governance tracking systems (Tokenomics) to monitor and cap LLM operating costs within strict platform operational limits

    • Financial & Compliance Guardrails: Architect execution boundaries and strict segregation-of-duties workflows for SOX-adjacent processes (e.g., Journal Entry generation vs. human approval)

    • System Integration & Action Routing: Oversee the architecture of the platform’s Action Gateway—handling direct API invocations, event-driven workflows, and fallback ticketing (Jira, Slack, Teams)

    • Technical Leadership & Standards: Set coding, testing, and formatting standards across application repositories. Mentor Senior and Mid-level AI engineers and drive code reviews enforcing RFC standard error formats, API contracts, and schema compliance

    Requirements

    • Experience: 8+ years of software engineering experience with 3+ years in a technical leadership capacity building multi-agent AI systems, FinOps tools, or LLM-powered platforms

    • Frameworks & Languages: Advanced proficiency in Python 3.11+, FastMCP, FastAPI, and Pydantic. Prior experience with object-oriented enterprise languages (e.g., Java) for seamless integration with core platform services and backend APIs

    • AI/LLM Architecture: Hands-on experience with Google ADK, Vertex AI, LiteLLM Gateway, Model Armor guardrails, prompt engineering, structured tool output parsing, and agent execution boundaries

    • Data & Cloud Platforms: Deep familiarity with the GCP ecosystem (BigQuery, GKE, Workload Identity), SQL schema design (FOCUS standard preferred), and partitioned/clustered OLAP architectures

    • Security & Governance: Experience implementing Zero Trust authentication (OAuth/KSA-to-GSA), RBAC, immutable audit logging, and API/MCP error specifications (RFC 7807/9457)

    • DevOps & Infrastructure: Proficiency with Docker builds, GKE deployment patterns, OpenTofu/Terraform, and CI/CD pipelines

    • Leadership Skills: Proven ability to coach, mentor, and influence teams beyond just writing and implementing solutions

    Nice to have

    • Experience with LangGraph / LangChain

    • Hands-on experience with Vertex AI

    • Working knowledge of modern DevOps and CI/CD practices

    • Familiarity with GCP infrastructure resources and their constraints, with the ability to identify optimal resources for designed AI agentic solutions

    We offer/Benefits

    • Medical, Dental and Vision Insurance (Subsidized)

    • Health Savings Account

    • Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)

    • Short-Term and Long-Term Disability (Company Provided)

    • Life and AD&D Insurance (Company Provided)

    • Employee Assistance Program

    • Unlimited access to LinkedIn learning solutions

    • Matched 401(k) Retirement Savings Plan

    • Paid Time Off – the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)

    • Paid Holidays - nine (9) total per year

    • Legal Plan and Identity Theft Protection

    • Accident Insurance

    • Employee Discounts

    • Pet Insurance

    • Employee Stock Purchase Program

    • If otherwise eligible, participation in the discretionary annual bonus program

    • If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program

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