VP, AI Strategy

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What the market looks like

We've tracked 200+ senior-level postings in AI engineering across the US over the last six months, concentrated in California, New York, and Texas. Organizations are actively building out AI strategy functions—particularly in professional services, technology, financial services, and healthcare—as they move beyond pilots toward scaled AI deployment. Senior-level leaders in this space typically land between $200K and $490K in base salary. The strongest candidates bring hands-on AI/ML execution experience paired with the ability to translate between technical teams and business stakeholders, often with track records scaling AI initiatives from inception through production.

Job responsibilities

• Own the strategic roadmap for AI adoption across the organization, identifying high-impact use cases and prioritizing initiatives aligned with business outcomes

• Partner with engineering, product, and data teams to architect and oversee the technical implementation of AI solutions at scale

• Build and lead the AI engineering team, setting technical standards, hiring talent, and fostering a culture of innovation and accountability

• Drive governance, risk, and compliance frameworks for AI systems, ensuring responsible development and regulatory alignment

• Communicate AI strategy and progress to the executive team and board, translating technical complexity into business impact

• Evaluate and integrate emerging AI tools, models, and infrastructure to maintain competitive advantage

• Establish metrics and KPIs to measure AI initiative success and inform resource allocation decisions

Candidate requirements

• 10+ years in AI/ML engineering, data science, or AI architecture roles, with at least 3+ years in a leadership or IC architect capacity

• Demonstrated success shipping AI/ML systems to production in regulated or complex environments

• Strong technical fluency in machine learning frameworks, deployment infrastructure, and AI operations (MLOps)

• Experience building and scaling technical teams, with comfort hiring and developing engineers

• Proven ability to bridge technical and business conversations, translating strategy into execution roadmaps

• Track record navigating AI governance, ethical considerations, and organizational change management