Fractional Chief AI Officer

Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we'll add you to our candidate network and may reach out when relevant roles come up.

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What the market looks like

We've tracked 100+ executive-level AI strategy postings in the last six months across the US, with particular concentration in California, New York, and Texas. Organizations hiring fractional Chief AI Officers span technology, financial services, professional services, manufacturing, and life sciences—each seeking external strategic guidance to build or refine their AI roadmaps without committing to a full-time executive hire. Compensation for fractional engagements typically ranges from $250–$400 per hour depending on scope and seniority. The strongest candidates bring hands-on experience translating AI opportunity into business outcomes, comfort operating at board and C-suite levels, and the ability to work autonomously with limited operational overhead.

Job responsibilities

• Shape and articulate a multi-year AI strategy aligned with business objectives, competitive positioning, and organizational capability

• Assess current state AI/ML adoption, talent, infrastructure, and governance; identify gaps and recommend phased roadmaps

• Partner with C-suite and board stakeholders to define AI investment priorities, success metrics, and risk mitigation

• Build or advise on AI governance, ethics, and compliance frameworks; ensure responsible deployment across the organization

• Mentor internal leaders and emerging AI talent; transfer strategic and operational knowledge to permanent teams

• Drive cross-functional alignment on AI use cases; help prioritize pilots and production deployments

• Track industry trends, competitive AI adoption, and emerging technologies; advise on make-vs-buy decisions and vendor partnerships

Candidate requirements

• 10+ years in AI, machine learning, data science, or adjacent technical leadership roles; minimum 5 years in a strategy, advisory, or executive capacity

• Demonstrated success building or scaling AI/ML programs from conception through production; hands-on familiarity with data infrastructure, model development, and deployment

• Experience operating at C-suite and board levels; comfort translating technical AI concepts for non-technical audiences and vice versa

• Track record of defining AI strategy, building business cases, and securing investment for AI initiatives

• Strong understanding of AI governance, risk, ethics, and regulatory landscape (e.g., data privacy, bias, model explainability)

• Ability to work independently, manage stakeholder relationships autonomously, and adapt to varied organizational contexts and maturity levels