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Kraft Heinz

Group Lead, AI Governance

Toronto, ON, Canada

Pay: $146,300.00 - $182,900.00
Job type: Full-time
Apply by: Oct 29, 2026
Posting language: English
Posted: Sep 29, 2026

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Original job description

Job Description

Group Lead, AI Governance at a glance..

Location: Toronto, ON

Hybrid: 3 days/week

The Kraft Heinz Information Technology organization is hiring a Group Lead, AI Governance to establish and operate the technical governance, platform controls and support model that enable safe, responsible and scalable use of AI across the enterprise. Based in Toronto, this leader will connect policy to day-to-day engineering practice across enterprise productivity AI, low-code agents and production-grade AI/ML solutions.

This is a hands-on leadership role (approximately 60% execution and 40% strategy). You will own the control framework and operating routines for platforms such as Microsoft 365 Copilot, Claude Enterprise, Microsoft Copilot Studio, Azure AI services and engineering patterns built with frameworks and observability tools such as LangGraph and LangSmith. You will partner with AI engineering, MLOps, security, legal, privacy, enterprise architecture, product and business teams to make risk-based decisions, remove delivery friction and ensure controls remain effective throughout the AI lifecycle.

What's on the menu?

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.

Recipe for success – apply now if this sounds like you!

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Technology, Cybersecurity, or related field (advanced degree an asset)
7+ years of experience across MLOps, machine learning 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
Experience leading people, vendors, or matrixed delivery teams; developing practical standards that improve safety and delivery velocity
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
Knowledge of agentic AI risks and controls (permissions, tool access, prompt injection, data leakage, autonomous actions, human approval points, end-to-end traceability)
Knowledge of data privacy, cybersecurity, model risk, third-party risk, intellectual property, regulatory compliance, AI FinOps, and business continuity considerations
Pragmatic risk leadership style that preserves strong controls without unnecessary friction for delivery teams
Comfort moving between executive-level governance discussions and detailed technical reviews with engineers and platform teams
Structured operator mindset (clear ownership, repeatable processes, measurable service levels, disciplined follow-through)
Sound judgment under ambiguity (escalating material issues, making proportionate recommendations, documenting defensible decisions)
Influential, cross-functional collaborator (Technology, Legal, Security, Privacy, Audit, Procurement, Data, and business functions)
Curious, current, and hands-on with a continuous-improvement mindset for fast-changing AI technologies and risks
Preferred: experience applying NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894, Microsoft Responsible AI guidance, or comparable AI governance frameworks
Preferred: relevant certification in Azure, security, privacy, risk, audit, project management, or AI governance

Our Total Rewards philosophy is to provide a meaningful and flexible spectrum of programs that equitably support our diverse workforce and their families and complement Kraft Heinz’ strategy and values.

New Hire Base Salary Range

$146,300.00 - $182,900.00

Bonus: This position is eligible for a performance-based bonus as provided by the plan terms and governing documents.

The compensation offered will take into account internal equity and may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors

Benefits: Coverage for employees (and their eligible dependents) through affordable access to healthcare, protection, and saving for the future, we offer plans tailored to meet you and your family’s needs. Coverage for benefits will be in accordance with the terms and conditions of the applicable plans and associated governing plan documents.

Wellbeing: We offer events, resources, and learning opportunities that inspire a physical, social, emotional, and financial well-being lifestyle for our employees and their families.

Benefits

You’ll be able to participate in a variety of benefits and wellbeing programs that may vary by role, country, region, union status, and other employment status factors, for example:

Physical - Medical, Prescription Drug, Dental, Vision, Screenings/Assessments
Social - Paid Time Off, Company Holidays, Leave of Absence, Flexible Work Arrangements, Recognition, Training
Emotional – Employee Family Assistance Program, Wellbeing Programs, Family Support Programs
Financial -Savings/Pension, Life, Accidental Death & Dismemberment, Disability, Discounted Perks

Location(s)

Toronto - Queen's Quay - Headquarters

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes. In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact NAZTAOps@kraftheinz.com for assistance.

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More about this job

Responsibilities

Lead the technical AI governance and platform support function, translating policies and risk requirements into practical controls, lifecycle processes, standards, and evidence requirements. Govern enterprise AI platforms and custom solutions, oversee risk reviews and incident response, and partner across technical and control teams to monitor effectiveness and improve responsible AI practices.

Requirements

Requires a bachelor’s degree in a relevant technical field and at least seven years of experience in areas such as MLOps, machine learning engineering, cloud or platform engineering, or technology risk, including responsibility for production AI/ML systems. Candidates should bring enterprise AI governance expertise, hands-on knowledge of generative and agentic AI, cloud and identity controls, lifecycle operations, and strong cross-functional leadership and communication skills.

Skills

AI Governance
MLOps
LLMOps
AI Risk Management
Responsible AI
Cloud Engineering
Identity and Access Management
CI/CD
Generative AI
Agentic AI
Observability
Incident Management
Technical Project Management
Data Privacy
Cybersecurity
Cross-Functional Leadership

Benefits

Medical Insurance
Prescription Drug Coverage
Dental Insurance
Vision Insurance
Paid Time Off
Company Holidays
Leave of Absence
Flexible Work Arrangements
Employee Recognition
Training
Employee and Family Assistance Program
Wellbeing Programs
Family Support Programs
Savings and Pension Plans
Life Insurance
Accidental Death and Dismemberment Insurance
Disability Insurance
Discounted Perks
Performance-Based Bonus

Visa sponsorship

Not detected in the job text

Keywords

Microsoft 365 Copilot
Claude Enterprise
Microsoft Copilot Studio
Azure AI Services
LangGraph
LangSmith
MLOps
LLMOps
NIST AI RMF
ISO/IEC 42001
ISO/IEC 23894
Responsible AI
AI Risk Management
AI Governance Frameworks
Generative AI
Agentic AI
Retrieval-Augmented Generation
Prompt Engineering
Context Engineering
AI Evaluations
Guardrails
Observability
Identity and Access Controls
CI/CD
Incident Management
Data Privacy
Cybersecurity
Third-Party Risk
AI FinOps
Model Lifecycle Management

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