Manager, AI Operations - Hybrid

8+ years of experience in large, enterprise-scale environments (public or private sector), supporting complex platforms with high reliability and uptime requirements.

Hands-on experience designing, implementing, and operating AI-enabled platforms, including:
Generative AI

Agentic AI (copilots, autonomous agents, digital assistants)

AI/ML workloads in cloud environments

Experience establishing greenfield platformsrather than inheriting mature legacy solutions understanding how to design for sustainability from day one.

Proven experience operationalizing AI from pilot to production, including:
Defining AI infrastructure architecture and standards

Implementing governance, privacy, security, and responsible AI controls

Monitoring performance, accuracy, bias, and risk

Incident response, root-cause analysis, and mitigation for AI-related issue.

Experience building operational sustainment models, including DR, business continuity, monitoring, alerting, and lifecycle management.

Experience leading technical teams, consultants, and vendors ideally including:
Acting as a technical lead or architect stepping into formal people leadership

Building new teams, defining roles, and shaping workforce plans

Comfortable managing a hybrid team model (internal staff + external consultants) in early-stage capability build-outs.

Deep understanding of AI infrastructure, cloud platforms, automation, and modern Dev Ops/MLOps practices.

Ability to work closely with Enterprise Architecture, Data & Analytics, Cybersecurity, Legal, and Application Development teams.

Strong grasp of operational best practices for mission-critical platforms, including:
High availability

Performance optimization

Cost management and Fin Ops

Secure access and permissioning

Able to define and evolve a long-term AI operations strategy aligned to enterprise goals.

Thinks beyond tools and experiments focuses on platform, governance, and sustainability.

Designs systems that are “living and breathing,” avoiding set-and-forget implementations.

Strong focus on stability, reliability, and 24x7 readiness.

Comfortable responding to incidents and outages when required.

Experienced in defining KPIs, dashboards, and metrics to track AI adoption, value realization, and operational health.

Credible technical leader who can earn trust from engineers, architects, and senior executives.

Able to lead through ambiguity, set direction where none exists, and bring structure to emerging domains.

Demonstrated ability to balance innovation with risk management and operational discipline.

Exceptional ability to translate complex AI and technical concepts into clear, plain-language insights.

Confident presenter to senior leadership, capable of securing buy-in for new platforms and governance models.

Strong collaborator who can align diverse stakeholders around shared standards, workflows, and approval processes.

Accountable and pragmatic:
Takes ownership, follows through, and delivers results.

Calm under pressure:
Handles high-visibility issues and operational incidents with confidence.

Curious and adaptable:
Continuously learns in a fast-evolving AI landscape.

Collaborative and respectful:
Models WorkSafeBC’s values in leadership, communication, and decision-making.

Business-oriented:
Always connects technical decisions to business value, impact, and outcomes.

Bachelor’s degree in Computer Science, Artificial Intelligence, Engineering, Business Technology, or related discipline.

Master’s degree preferred but not required.

Equivalent combination of education and experience considered, especially for candidates with strong hands-on AI platform leadership.