AI Ops Manager - New York
AutomatticNew York City$115k – $190kPosted 22 March 2026
Job Description
Location: NYC NoHo Office (5 days a week)
About This Opportunity
We're building something unusual at Automattic : an AI-native culture at a 1,500-person company that powers 40% of the web. Not just adopting AI tools, but fundamentally transforming how we work and ship products at scale.
You’ll own the operational infrastructure that makes this possible. The messy, critical work between “we should use AI” and “we’re actually using AI effectively across 1,500 people”: privacy reviews, tool evaluations, policy development, vendor coordination, adoption tracking, and being the person who can answer “should we use this tool?” and “how should we approach this?”
This isn’t traditional program management. You’re building the governance frameworks and operational practices that help a distributed, highly technical organization move faster with AI while managing risk appropriately. You’ll work in-person with our Head of AI and NYC AI team while supporting AI adoption globally.
Why This Role Matters
Most companies are still asking “should we allow AI tools?” Automattic is asking “how do we use AI tools exceptionally well at scale while managing risk appropriately?” You’ll build the operational foundation that enables 1,500 people to move faster, work smarter, and compete in an AI-driven world.
Your decisions will have unusual leverage: shaping company-wide policy, creating governance infrastructure, and directly impacting how hundreds of millions of users experience AI in Automattic products.
What You’ll Do
Own change management: design adoption campaigns, identify blockers to AI-native workflows, create enablement resources that move teams from experimentation to integration.
Own AI governance: triage privacy questions, coordinate tool evaluations with Legal and Security, develop policy frameworks, guide procurement decisions.
Build operational infrastructure: create processes where none exist, document decisions so teams can move faster, track adoption metrics and ROI.
Manage cross-functional stakeholders: coordinate across Engineering, Product, Legal, Finance, and HR on AI initiatives and resource allocation.
Serve as the central point of contact for AI questions across the company; translate ambiguous situations into clear guidance and actionable decisions.
Report to leadership on AI adoption status, risks, and opportunities; facilitate strategic planning.
Create dashboards, documentation, and operational playbooks that scale across a distributed organization.
You’ll Thrive Here If You
Have 3–5+ years in technical program management or product operations at tech companies, managing complex initiatives with multiple stakeholders.
Bring strong operational instincts. You build processes, create frameworks, and make chaos manageable.
Excel at stakeholder management. Comfortable presenting to executives, facilitating cross-team discussions, influencing without direct authority.
Navigate legal, privacy, and security considerations around new technology with confidence.
Are data-driven. You track metrics, analyze trends, and use data to inform strategy.
Thrive on bringing order to chaos. You’re energized by building systems that scale and being the “go-to person” for complex situations.
Technical Experience We Value
Experience managing AI/ML initiatives or evaluating technical products (you don’t need to code, but should understand technical implications).
Background in vendor evaluation, procurement processes, or technology governance.
Track record building operational infrastructure or governance frameworks from scratch.
Experience working with distributed/remote teams and async communication tools.
Startup experience wearing multiple operational hats.
Bonus Points
Previous work in management consulting, strategy, or business operations.
Experience with AI tools in a professional context (understanding the landscape, not necessarily deep technical usage).
Background supporting engineering or product teams ... (truncated, view full listing at source)
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