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EPAM Systems

Lead AI Engineer - TCO Agent Platform

Canada

Salary range: CA$150,000-CA$200,000. · Full-time

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Job details

Pay: Salary range: CA$150,000-CA$200,000.
Job type: Full-time
Experience: 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
Posting language: English
Posted: Sep 22, 2026

Original job 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.

Req.#1087619193

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

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.

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 job description 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.

EPAM Canada welcomes and encourages applications from candidates with disabilities. Please contact WFA Human Resource CA WFAHRCA@epam.com 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.

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

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More about this job

Responsibilities

Lead the architecture and implementation of an eight-agent FinOps AI platform, including orchestration, LLM governance and cost controls, financial compliance guardrails, and action routing across cloud services and enterprise tools. Set engineering standards, oversee code reviews, and mentor engineers while collaborating with product and architecture teams.

Requirements

Requires 8+ years of software engineering experience, including 3+ years in technical leadership building multi-agent AI systems, FinOps tools, or LLM-powered platforms. Candidates should have advanced Python and AI/cloud platform expertise, experience with security and financial governance, and the ability to mentor and influence engineering teams.

Skills

Multi-Agent AI Architecture
Python
FastMCP
FastAPI
Pydantic
Google ADK
Vertex AI
LiteLLM
Model Armor
Prompt Engineering
GCP
AWS
BigQuery
GKE
Workload Identity
Terraform

Benefits

Extended Healthcare and Prescription Drug Coverage
Dental and Vision Coverage
Healthcare Spending Account
Life and Accidental Death and Dismemberment Insurance
Employee Assistance Program
Telehealth
Short-Term Disability Insurance
Long-Term Disability Insurance
Paid Time Off
Registered Retirement Savings Plan with Company Match
Maternity, Parental, and Adoption Leave Top-Up
Employee Stock Purchase Program
Critical Illness Insurance
Employee Discounts
LinkedIn Learning Access

Visa sponsorship

Not detected in the job text

Keywords

Multi-Agent Systems
FinOps
Python 3.11+
FastMCP
FastAPI
Pydantic
Google ADK
Vertex AI
LiteLLM Gateway
Model Armor
Prompt Engineering
Tokenomics
GCP
AWS
BigQuery
GKE
Workload Identity
FOCUS Standard
SQL Schema Design
OLAP Architectures
Zero Trust
OAuth
RBAC
Immutable Audit Logging
RFC 7807
RFC 9457
Docker
OpenTofu
Terraform
CI/CD

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