Head of AI Operations & Governance

Shield; Oslo; On-site; NOK 2,667,000 - 4,000,000; Full time

Job summary

Shield AI is seeking a Director of AI Operations & Governance to operationalize and govern our workplace AI ecosystem across all AI initiatives. Reporting to the VP of Workplace AI, this role will own license and platform operations, AI governance, security posture, and ongoing lifecycle management of AI tools that support Shield AI's business functions.

This role requires significant hands‑on technical capability across the machine learning lifecycle and the ability to evaluate, tune, and

Qualifications

• 15+ years in platform operations, ML/AI operations, DevOps, or SaaS sustainment roles, including significant leadership experience.
• Direct, hands-on experience developing, training, fine‑tuning, or evaluating machine learning models or generative AI systems.
• Working knowledge of AI/ML research practices and ability to apply to production decision-making.
• Strong governance, security, and cost-optimization experience for SaaS or AI tools.

Responsibilities

• Own AI sustainment and governance for workplace AI tools and build the team to scale it.
• Manage licenses and entitlements: monitor usage, optimize allocations, and coordinate with Finance.
• Monitor production usage and recommend roadmap items based on real-world data.
• Lead AI governance practices in partnership with Security, Legal, and HR.
• Define playbooks, SLAs, and incident response procedures for AI systems.

Skills

Leadership experience

ML/AI operations

Executive communication

Hybrid work management

Tools

n8n

AI orchestration tools

Job description

Shield AI is seeking a Director of AI Operations & Governance to operationalize and govern our workplace AI ecosystem across all AI initiatives. Reporting to the VP of Workplace AI, this role will own license and platform operations, AI governance, security posture, and ongoing lifecycle management of AI tools that support Shield AI's business functions.

This role requires significant hands‑on technical capability across the machine learning lifecycle and the ability to evaluate, tune, and