Director of AI Operations & Governance
- Role
- AI / ML
- Employment
- Full-time
Open to US only. Set where you work from to check your eligibility.
No BS summary
Own license and platform operations, AI governance, security posture, and ongoing lifecycle management of AI tools. Responsible for "post-dev-ops" for AI, ensuring systems are reliable, compliant, secure, and continuously improving. Build and lead the team responsible for AI sustainment. Requires significant hands-on technical capability across the machine learning and generative AI lifecycle.
Core skills
Required languages
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. The role will be the central owner of "post–dev-ops" for AI, ensuring systems are reliable, compliant, secure, and continuously improving in line with production usage and business needs, while building and leading the team responsible for AI sustainment. This role requires significant hands-on technical capability across the machine learning and generative AI lifecycle — not just program oversight. The Director must be able to credibly evaluate, tune, and troubleshoot models and AI systems at a technical level in order to govern them effectively, partner with engineering, and make sound tradeoffs between reliability, performance, cost, and risk.
What you'll do
- Operationalize and govern the workplace AI ecosystem across all AI initiatives.
- Own license and platform operations for AI.
- Manage AI governance.
- Oversee AI security posture.
- Manage the ongoing lifecycle of AI tools that support Shield AI's business functions.
- Own "post–dev-ops" for AI, ensuring systems are reliable, compliant, secure, and continuously improving in line with production usage and business needs.
- Build and lead the team responsible for AI sustainment.
What they require
- Significant hands-on technical capability across the machine learning and generative AI lifecycle — not just program oversight.
- Ability to credibly evaluate, tune, and troubleshoot models and AI systems at a technical level in order to govern them effectively.
- Ability to partner with engineering.
- Ability to make sound tradeoffs between reliability, performance, cost, and risk.
United States aerospace and defense technology company