Director, AI Strategy

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What The Market Looks Like AI strategy leadership is one of the hottest segments in the job market right now — we’ve tracked 4,400+ director and VP-level AI strategy postings in the last six months, concentrated across technology, financial services, professional services, and manufacturing. New York and San Francisco are dominant hiring hubs, with San Francisco, New York, and the broader Bay Area leading by volume. Compensation for directors in this space lands around $240,000 median, with top-tier opportunities reaching $450,000+. The strongest candidates bring a mix of hands-on AI/ML literacy, proven ability to build and operationalize AI initiatives at scale, and the strategic chops to translate business needs into AI roadmaps — they’re equally comfortable in the boardroom and in technical deep dives.

Job Responsibilities

• Own the end-to-end AI strategy roadmap: define use cases, prioritize initiatives, and align with business objectives across the organization
• Lead cross-functional teams (product, engineering, data science, ops) to scope, build, and deploy AI solutions into production
• Drive governance, risk assessment, and compliance frameworks for AI systems — including model validation, bias testing, and regulatory alignment
• Partner with the C-suite and board on AI investment decisions, competitive positioning, and market opportunities
• Build and mentor the AI and data science teams, setting technical standards and fostering a culture of experimentation
• Integrate generative AI, LLMs, and emerging foundation models into existing products and operations
• Track industry trends, emerging technologies, and competitive AI moves — communicate implications and opportunities back to leadership

Candidate Requirements

• 7+ years building and scaling AI/ML initiatives, with 3+ years in a leadership or strategy role driving AI adoption at the enterprise level
• Deep technical fluency in machine learning, generative AI, and LLMs — you’ve worked alongside data scientists and ML engineers and understand what’s buildable and what isn’t
• Proven track record shipping AI products or features to production and measuring their business impact
• Experience translating business problems into AI opportunities and vice versa — ability to lead both technical and non-technical stakeholders
• Familiarity with AI governance, model risk, fairness, and compliance considerations in highly regulated or risk-sensitive environments
• Strong communication and executive presence — you can speak credibly to C-suite, boards, and technical teams in the same day