Director, AI Strategy
United States · Remote
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 4,400+ senior-level AI strategy postings in the United States over the last six months, with strongest hiring in California, New York, and Texas across technology, professional services, and financial services. These roles typically land between $240,000 and $450,000 in total compensation. The strongest candidates bring a mix of hands-on AI/ML fluency, real experience translating emerging AI capabilities into business value, and proven ability to influence cross-functional leaders—not just deep technical depth or pure strategy consulting experience alone.
Job responsibilities
Own the organization's AI strategy roadmap: define where and how AI creates competitive advantage, set investment priorities, and communicate the vision to the board and leadership team.
Partner with engineering, product, and business leaders to identify and scope high-impact AI use cases, from AI-augmented customer experiences to operational automation and data monetization.
Lead the build or integration of AI capabilities: oversee model selection, vendor evaluation, build-versus-buy decisions, and technical architecture choices alongside your engineering partners.
Drive organizational readiness: build cross-functional governance, define data and infrastructure requirements, establish ethical AI and risk-management frameworks, and upskill teams on AI fundamentals.
Own portfolio performance and iteration: measure AI initiative impact against business KPIs, refine strategy based on learnings, and allocate resources to highest-ROI opportunities.
Represent the organization externally: engage with customers, investors, and industry peers on AI capabilities and strategy, and stay current with rapid shifts in AI technology and competitive landscape.
Shape talent and culture: recruit and retain AI-skilled leaders and engineers, sponsor learning programs, and foster a culture of experimentation and measured risk-taking.
Candidate requirements
8+ years in AI, machine learning, data science, or closely related technical leadership roles—hands-on experience building, shipping, or scaling AI/ML systems, not pure management or consulting.
Proven track record translating AI/ML capabilities into measurable business outcomes: you've owned use cases from conception through production and can articulate the financial or operational impact.
Fluency in current AI/ML tools, techniques, and landscape: you stay current with model architectures, LLMs, vector databases, and deployment patterns, and can evaluate new tools critically.
Experience leading cross-functional teams and influencing without direct authority: you've collaborated with product, engineering, finance, and executive leadership to unblock decisions and align competing priorities.
Ability to communicate complex technical concepts to non-technical audiences—board members, business unit leaders, customers—without oversimplifying or overpromising.
Comfort with ambiguity and rapid change: you've navigated the early stages of emerging technology adoption, adapted strategy as the landscape shifted, and made good calls with incomplete information.