About the Role
The company is hiring an AI Ops / AI Engineering Manager to lead our internal AI engineering function and turn AI from scattered tools into a governed operating system for the company.
In this role, you will own the internal AI and automation roadmap, manage AI Engineers, prioritize automation requests, govern agent usage, and ensure AI systems improve productivity without creating security, quality, or operational risk. This is a hands-on leadership role for someone who can connect executive priorities, business workflows, engineering execution, and practical AI governance.
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What You’ll Do
- Own the internal AI and automation roadmap across departments.
- Manage the AI Engineering team, assign priorities, review delivery quality, and maintain technical standards.
- Create governance for AI agents, automations, prompts, data access, permissions, and usage policies.
- Prioritize automation requests based on business impact, risk, urgency, and reusability.
- Partner with department heads to identify high-value workflows across sales, recruiting, finance, delivery, marketing, and executive operations.
- Ensure AI workflows are documented, tested, monitored, and supportable.
- Track adoption, time saved, failure rates, user satisfaction, and operational impact.
- Coordinate with IT/security and system owners where security, access, SSO, device, or system ownership overlaps.
What We’re Looking For
- Experience managing engineers, automation builders, AI teams, RevOps systems teams, or technical operations teams.
- Strong understanding of AI tools, APIs, automation, integrations, data flows, permissions, and business process design.
- Ability to translate executive priorities into technical workflows and ship usable systems quickly.
- Strong governance mindset across security, privacy, reliability, documentation, and change management.
- Clear communication and comfort working directly with executives, technical teams, and business stakeholders.
Nice to Have
- Experience deploying internal AI agents or automation programs inside a fast-growing company.
- Experience with Notion, Odoo, Salesforce or other CRM systems, RevOps workflows, finance workflows, or consulting delivery operations.
- Comfort training business teams and driving adoption, not just managing technical output.
What Success Looks Like
- High-impact automations are shipped and adopted by departments.
- Manual work is reduced and execution speed improves across the company.
- AI governance, documentation, access controls, and quality standards are clear.
- AI Engineers are productive, focused, and delivering high-quality systems.
- AI systems are reliable, monitored, and maintain a low failure rate.
First 90 Days
In your first 90 days, you will:
- Audit existing AI tools, agents, automations, and informal workflows.
- Create the first AI roadmap and prioritization model.
- Define governance standards for access, data, documentation, testing, and monitoring.
- Ship the first wave of business-critical automations with the AI Engineers.
- Create a weekly AI Ops review with clear metrics, priorities, and blockers.
