Director, AI Strategy

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What the market looks like

Over the last six months, we've tracked 1,300+ senior-level postings in AI engineering across the United States, with concentrations in California, New York, and Texas. Organizations across professional services, technology, financial services, and life sciences are competing hard for leaders who can translate AI capability into business outcomes. Compensation for this cohort typically ranges from $240K to $410K annually. The strongest candidates combine hands-on technical depth with proven ability to connect engineering roadmaps to strategic priorities, and they bring experience building or scaling AI teams through organizational change.

Job responsibilities

• Own the AI engineering strategy and roadmap, defining technical priorities that align with business goals and competitive positioning

• Build and lead a team of AI engineers, architects, and specialists—hiring, mentoring, and setting standards for technical rigor and delivery

• Partner with product, data science, and business stakeholders to translate strategic initiatives into concrete AI/ML projects and ship them to production

• Drive architecture decisions, technology evaluation, and infrastructure investments that enable scalable, secure, and maintainable AI systems

• Establish governance, tooling, and MLOps practices that accelerate development velocity while managing risk and compliance

• Lead cross-functional efforts to integrate AI capabilities into existing products and platforms, or build new AI-first solutions

• Communicate progress, capability, and technical trade-offs to executives and board stakeholders; translate AI potential into business value

Candidate requirements

• 7+ years of experience in AI/ML engineering, platform engineering, or data systems at scale—with at least 3 years in a leadership or senior architect role

• Proven track record building and shipping AI/ML systems to production; deep familiarity with LLMs, transformers, or other modern AI architectures

• Experience leading and scaling technical teams through hiring, performance, and organizational change

• Strong foundation in software engineering fundamentals (architecture, testing, deployment, operations) and ability to set engineering standards

• Demonstrated ability to translate between technical depth and business strategy; comfortable engaging executives on ROI, risk, and AI capability roadmaps

• Experience working across organizations (product, data science, infrastructure, security) to unblock AI adoption and integration