AI Governance Group Lead — Hybrid Toronto

Kraft Heinz

Toronto

Hybrid

CAD 208,000 - 260,000

Full time

7 days ago

Be an early applicant

A complete application in a minute

Tailored resume and cover letter, ready to send.

Get past ATS filters

Benefits offered by this job

Healthcare coverage

Flexible work arrangements

Paid time off

Wellbeing programs

Job summary

Kraft Heinz is seeking a Group Lead, AI Governance in Toronto to establish and operate a technical governance and platform controls framework for safe, responsible, scalable AI across the enterprise. This hands-on leader will drive policy-to-engineering in productivity AI, low-code agents, and production AI/ML solutions, blending 60% execution with 40% strategy.

The role partners with AI engineering, MLOps, security, privacy, legal, and enterprise architecture to balance risk and delivery,

Qualifications

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Technology, Cybersecurity, or related field
7+ years of experience across MLOps, ML engineering, data science, cloud engineering, platform engineering, technology risk, or related disciplines, including responsibility for production AI/ML systems
Hands-on experience designing, deploying, operating, or governing AI/ML platforms in a large, matrixed enterprise environment
Practical understanding of AI risk management and responsible AI principles (accountability, transparency, privacy, security, reliability, safety, fairness, human oversight)
Experience with cloud and identity controls, CI/CD, model/agent lifecycle management, observability, incident management, and production support (preferably Microsoft Azure)
Experience with generative AI and agentic patterns (LLM applications, RAG, prompt/context engineering, tool use, agent workflows, evaluations, guardrails)
Working knowledge of Microsoft 365 Copilot and Copilot Studio; familiarity with Claude Enterprise, LangGraph, LangSmith, or comparable AI development/observability platforms strongly preferred
Demonstrated technical project/program management experience (driving cross-functional work, managing dependencies, translating ambiguous requirements into executable plans)
Strong written and verbal communication skills; able to explain technical risk, control design, and trade-offs to engineers, control functions, and senior business stakeholders
Enterprise AI governance expertise (operating models, control frameworks, risk tiering, exception management, assurance, evidence-based decision making)
MLOps and LLMOps expertise across development, deployment, monitoring, evaluation, change control, support and retirement
AI platform governance experience for employee productivity tools, low-code agents, third-party AI services and custom production applications

Responsibilities

Lead the technical AI governance and platform support function, setting priorities, service expectations, operating routines and clear accountability across enterprise AI tools and custom AI solutions
Translate AI policies, risk appetite and regulatory obligations into practical engineering standards, approval criteria, platform configurations, reusable controls and evidence requirements
Own risk-tiered lifecycle governance from intake and experimentation through production approval, change management, monitoring, incident response and retirement, with proportionate checkpoints based on use-case criticality
Establish and maintain an enterprise inventory of AI tools, models, agents, use cases, owners, data dependencies, risk classifications, approvals and material changes
Support relevant teams on technical controls for identity and access, least privilege, data protection, secrets management, environment separation, vendor integrations, human oversight, logging, traceability and audit evidence
Set standards for AI evaluation and production readiness, including quality, safety, reliability, security, privacy, latency, cost and business acceptance criteria; ensure exceptions are documented, time-bound and remediated
Build observability and governance patterns for agentic systems, including prompt and response tracing, tool-call visibility, evaluation datasets, failure analysis, escalation paths and controls for autonomous actions
Govern and support AI platforms including Microsoft 365 Copilot, Claude Enterprise, Copilot Studio, Azure-based AI services and custom solutions using LangGraph, LangSmith and related MLOps/LLMOps capabilities
Lead AI platform intake, access and support processes; triage incidents and control gaps, coordinate root‑cause analysis, track corrective actions and communicate material risks to the appropriate governance bodies
Partner with Legal, Privacy, Cybersecurity, Procurement, Internal Audit, Data Governance, Enterprise Architecture and business owners on use-case reviews, third-party assessments, control testing and audit readiness
Define governance metrics and service health indicators covering inventory completeness, review cycle time, control compliance, incidents, exceptions, evaluation coverage, adoption, consumption and remediation progress
Lead cross-functional initiatives and technical projects, managing scope, milestones, dependencies, decisions and stakeholder communications while coaching engineers and analysts on responsible AI practices
Monitor developments in AI regulation, standards, platform capabilities and emerging risks; assess their relevance and drive updates to controls, playbooks and technical roadmaps