Fractional Head of AI
United States · Remote · Fractional
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What the market looks like
We've tracked 100+ executive-level AI strategy postings in the United States over the last six months, with hiring concentrated in technology, professional services, and financial services hubs like San Francisco and New York. Organizations are moving past AI pilot phases and building permanent strategy functions—fractional heads of AI are particularly in demand as companies scale their AI initiatives without committing to a full-time executive hire. The strongest candidates bring direct experience shipping AI products or embedding AI into existing business operations, paired with the executive presence to translate between technical teams and the C-suite. Compensation for this seniority typically ranges from $250–$400 per hour, with flexibility to scale engagement based on strategic need.
Job responsibilities
Own the AI strategy roadmap: define where and how AI creates competitive advantage, prioritize initiatives, and align investment with business outcomes.
Build and mentor the AI leadership team: recruit and develop heads of AI/ML engineering, data science, and MLOps; establish performance metrics and accountability.
Drive cross-functional adoption: partner with product, engineering, finance, and business units to embed AI into workflows and unlock value from early wins.
Communicate AI progress to the board and C-suite: translate technical progress into business impact, manage expectations, and secure budget and stakeholder buy-in.
Shape governance and risk frameworks: establish guardrails for model deployment, data quality, bias mitigation, and compliance—moving at speed without sacrificing rigor.
Benchmark and scale: track competitive landscape, emerging tools and techniques, and recommend make-vs.-build decisions and vendor partnerships.
Accelerate time-to-value: unblock technical teams, remove organizational friction, and maintain momentum as AI moves from experimental to production.
Candidate requirements
10+ years building and scaling AI or machine learning functions, with at least 3–5 years in a head-of-function or VP-level role.
Hands-on track record shipping AI products or embedding AI into core business operations; deep familiarity with the full lifecycle from strategy through production.
Proven ability to recruit, mentor, and scale technical teams; experience managing multiple sub-functions (engineering, data science, MLOps, or analytics).
Strong business acumen and executive communication skills; comfortable translating between technical depth and board-level strategic thinking.
Experience navigating organizational change: moving companies from AI exploration to scaled, sustainable AI practices with clear ROI.