AI Governance & Risk Manager
General Dynamics Missions System International · Ottawa, ON, Canada · hybrid
Build bold. Deliver impact. Win together.
At General Dynamics Mission Systems–Canada, we’re not just engineering technology — we’re shaping the future of defence and security. Our teams design and deliver advanced, mission-critical solutions that enhance national security, strengthen communities, and protect the people we serve.
If you’re looking for meaningful work that contributes to a safer, more secure world, you’ll find purpose here. Every day, your skills will directly impact programs that matter.
Reporting to the Chief Digital & Information Officer (CDIO), the Manager, AI Governance & Risk will lead the establishment, execution, and continuous evolution of the enterprise AI governance program.
At General Dynamics Mission Systems, governance is not viewed as a control mechanism designed to restrict innovation. Rather, governance provides the guardrails, accountability, and trusted operating framework within which ideation, experimentation, and creativity can thrive. The objective of this role is to enable the safe, responsible, and accelerated adoption of artificial intelligence across the enterprise while reducing organizational, regulatory, security, privacy, and operational risk.
This leader will serve as the organization’s primary authority for AI governance, partnering with business leaders, technologists, cybersecurity teams, legal counsel, privacy professionals, data practitioners, and operational stakeholders to ensure AI solutions deliver business value while meeting corporate, customer, and regulatory requirements.
The successful candidate will establish governance frameworks that are proportional to risk, enabling low-risk innovation to move quickly while ensuring appropriate oversight for higher-risk use cases. This role requires a blend of strategic leadership, risk management expertise, technical understanding of modern AI systems, and the ability to influence outcomes across the enterprise without direct authority.
The Manager, AI Governance & Risk will help position responsible AI as a business enabler and competitive differentiator, fostering an environment where innovation can scale with confidence.
Key Responsibilities
AI Governance Strategy & Leadership
- Develop and maintain the enterprise AI Governance Framework, including policies, standards, operating procedures, controls, and oversight mechanisms.
- Establish a scalable governance operating model supporting Generative AI, Agentic AI, Machine Learning, and Intelligent Automation initiatives.
- Provide strategic guidance to executive leadership regarding AI governance, responsible AI, regulatory developments, and enterprise risk.
- Drive organizational alignment around responsible AI principles and governance expectations.
- Serve as the primary escalation and decision-support authority for AI governance matters.
- Promote governance as an enabler of innovation, ensuring guardrails are practical, proportionate to risk, and focused on enabling positive business outcomes.
AI Risk Management
- Conduct and oversee AI risk assessments for new and existing AI systems, applications, platforms, and use cases.
- Develop and maintain AI risk classification and risk-tiering methodologies.
- Assess risks associated with Generative AI, Large Language Models, Agentic AI systems, autonomous decision-making, AI-enabled business processes, and third-party AI services.
- Develop mitigation strategies and remediation plans for identified risks.
- Maintain enterprise AI risk registers, issues logs, exceptions, and remediation tracking.
Responsible AI & Governance Operations
- Develop governance review processes that support rapid experimentation while ensuring appropriate safeguards.
- Establish AI intake, review, approval, and monitoring processes.
- Create reusable governance templates, assessment frameworks, playbooks, and guidance materials.
- Define governance requirements relating to human oversight, explainability, transparency, security, data privacy, intellectual property protection, model monitoring, and accountability.
- Build self-service governance capabilities that empower teams to assess and manage low-risk use cases efficiently.
Agentic AI Governance
- Develop governance approaches for agentic and autonomous AI systems.
- Assess AI capabilities involving tool calling, agent-to-agent communications, Retrieval-Augmented Generation, memory systems, external integrations, autonomous workflow execution, and human approval gates.
- Evaluate operational, technical, legal, and compliance risks associated with advanced AI architectures.
- Establish governance guardrails appropriate to system autonomy, decision reversibility, mission impact, and business risk.
Policy, Compliance & Regulatory Oversight
- Maintain AI governance policies and standards in alignment with organizational objectives.
- Monitor the evolving AI regulatory and compliance landscape.
- Translate regulatory, contractual, and corporate requirements into practical governance controls.
- Support enterprise compliance efforts relating to NIST AI RMF, NIST Cybersecurity Framework, CMMC, DFARS, ITAR, Controlled Goods, privacy legislation, export controls, ISO/IEC 42001, and customer-specific AI requirements.
- Coordinate governance evidence and reporting activities supporting audits and assessments.
Metrics, Reporting & Executive Communications
- Develop AI governance metrics, key performance indicators, and maturity measures.
- Produce executive-level reporting on governance effectiveness, emerging risks, compliance posture, and program health.
- Provide recommendations to leadership regarding governance priorities, investment opportunities, and risk treatment strategies.
- Develop dashboards and reporting mechanisms that demonstrate both risk reduction and innovation enablement outcomes.
Cross-Functional Collaboration
- Partner with leaders across Information Technology, Cybersecurity, Data & Analytics, Legal, Privacy, Engineering, Security, Contracts, Human Resources, and Business Operations.
- Facilitate governance review boards and stakeholder working groups.
- Provide coaching and guidance to project teams and business leaders adopting AI technologies.
- Foster a culture of responsible experimentation, ideation, creativity, and continuous learning.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Cybersecurity, Risk Management, Business Administration, Data Science, Engineering, or a related discipline.
- Minimum 10 years of relevant experience in AI governance, technology governance, cybersecurity, risk management, compliance, data governance, internal audit, enterprise architecture, or a related discipline.
- Demonstrated experience developing governance frameworks, policies, standards, or enterprise controls.
- Strong understanding of modern AI technologies, including Generative AI, Large Language Models, Agentic AI, Machine Learning, and Intelligent Automation.
- Experience conducting risk assessments and translating complex requirements into actionable, proportionate controls and guardrails.
- Strong understanding of enterprise governance, risk, and compliance principles.
- Excellent executive communication, presentation, stakeholder management, and influencing skills.
- Demonstrated ability to operate independently and drive cross-functional outcomes.
Preferred Qualifications
- Master’s degree in a related field.
- Experience establishing or operating an enterprise AI governance program.
- Experience within a regulated industry such as aerospace, defence, government, financial services, or critical infrastructure.
- Experience with Microsoft Copilot, Azure AI Foundry, OpenAI, Anthropic, Google AI, or similar enterprise AI platforms.
- Experience supporting enterprise AI adoption at scale.
- Familiarity with cloud governance, cybersecurity governance, and data governance programs.
- Active security clearance or the ability to obtain and maintain a securi