Head of AI Native Operations

Role

Head of AI Native Operations responsible for designing, operating, and scaling an AI-native internal operating system that embeds agentic automation into company processes. You will own the maturity model, standards, operating cadence, and evidence/assessment framework, lead a small senior team, and ensure standards are enforceable via automated mechanisms.

Key Responsibilities

• Own the maturity model end-to-end: rubric, scoring, evidence standard, and appeals path, producing a published assessment and a written plan for each team.
• Run assessments and commitments with department heads, converting assessments into named owners and dates.
• Define and publish the standards layer: how work is tracked, decisions are proposed/resolved, shared tooling adoption, and documentation retirement.
• Fix decision processes by defining stages, exit criteria, and closing mechanisms to prevent unresolved proposals.
• Run the operating cadence: automated weekly reporting, blockers-and-decisions forum, monthly leadership review, and quarterly board formats; replace meetings with reports where possible.
• Manage rollouts: private assessments followed by public transparency dates.
• Wire standards into onboarding so new cohorts arrive pre-trained.
• Build and direct a small team (two senior individual contributors: platform and enablement), including hiring, growth, and reviews.
• Measure and publish outcomes demonstrating how much coordination work agents absorb versus human program office cost.

How You’ll Think / Approach

• Recursive Thinking: write standards that feed enforcement and produce evidence used to grade compliance; your own team is assessed by the same model.
• Inversion Thinking: design standards with the assumption teams will route around them; focus on what will make teams adopt rather than whether the standard is ‘correct’.
• AI-Native Execution: direct agent workflows rather than doing manual work; validate agent workflow definitions, data models, and pull requests; working artifacts should be machine-readable files in version control.

Requirements

Must Have

• Experience running operating cadence and program discipline at companies of roughly ~200–800 people in remote/async environments.
• Built and operated agentic AI workflows others depended on; able to read/review agent workflow definitions, data models, and PRs.
• Track record of taking a standard from zero to company-wide adoption without direct authority over adopters.
• Exceptional async written communication skills; able to use documents as enforcement mechanisms.
• Comfortable being publicly graded by the systems you build.

Strong Signals

• Experience running a maturity model or capability assessment across teams you did not own and publishing results.
• Native experience with Git, Markdown, and Pull Requests.
• Experience permanently eliminating recurring meetings by replacing them with automated systems.
• Deep software engineering background is a plus but not required.

Success Metrics

• Standards are followed without manual chasing; non-compliance is visible automatically.
• Every team has an evidence-backed assessment, owner, and written path to the next level; appeals are handled publicly.
• Pre-committed transparency dates are honored across assessments.
• Net-negative meeting time across the organization by year-end.
• Two direct reports operate independently; at least one non-reference team runs a genuinely automated production workflow.

Benefits

• Fully remote role with global hiring, plus a WeWork membership or co-working allowance.
• ESOP (equity ownership) for employees.
• Tech allowance for equipment (laptop, monitor, headphones, etc.).
• Health benefits: company covers 100% for employees and 80% for dependents.
• Annual company off-sites.
• Flexible asynchronous work.
• Annual professional development / education allowance.