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 setting.

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.

Req.#(phone hidden)

The recruiting efforts for this position are intended to fill an existing vacancy for a new position.

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

- Extended Healthcare with Prescription Drugs, Dental and Vision, and Healthcare Spending Account (Company Paid)
- Life and AD&D; Insurance (Company Paid)
- Employee Assistance Program (Company Paid)
- Telehealth (Company Paid)
- Short-term Disability (Company Paid)
- Long-Term Disability
- Paid Time Off (including vacation and sick days)
- Registered Retirement Savings Plan (RRSP) with Company match
- Maternity/Parental/Adoption Leave Top-up
- Employee Stock Purchase Program
- Critical Illness Insurance
- Employee Discounts
- Unlimited access to LinkedIn learning solutions

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams,



contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

Engineer the Future with a Career at EPAM

This posting includes a salary range EPAM Canada would reasonably expect to pay the selected candidate. Individual compensation offers within the range are based on a variety of factors, including, but not limited to, experience, credentials, education, training, the demand for the role, skillset, and overall business and local labour market considerations. Most candidates are hired at a salary within the range disclosed.

Salary range: CA$150,000-CA$200,000. In addition, the details highlighted in this job posting above are a general description of all other expected benefits and compensation for the position.

EPAM Canada welcomes and encourages applications from candidates with disabilities. Please contact WFA Human Resource CA [email protected] if you have questions in this regard, or if you require an accommodation to complete the application process. Click here to review EPAM’s Accessibility for Ontarians with Disabilities Accessibility Policies and Multi-Year Access.

An artificial intelligence system is software that is developed with one or more techniques that can, for a given set of human-defined objectives, using algorithmic information processing, generate outputs such as content, predictions, recommendations, or decisions with varying levels of autonomy (“AI”). Tasks that humans have traditionally done by thinking and reasoning are increasingly being done by, or with the help of, AI to help create efficiencies.EPAM may use AI during the recruitment process, in connection with collecting or processing your personal data. Some (non-exhaustive) examples of tasks that EPAM may use AI for include conducting initial screening, creating transcripts of interviews, and assessing applications/CVs against defined criteria to make suggestions to the individuals evaluating your candidacy.Your personal data and the results of any processing are not shared with AI applications outside of EPAM infrastructure.

While EPAM may use AI to help create efficiencies during the recruitment process, EPAM does not use AI to make hiring decisions, which is done by EPAM Talent Acquisition and management.

📌 Lead AI Engineer — TCO Agent Platform (Canada)
🏢 EPAM Systems
📍 Canada