Heads up: this is not a live role. Axial Search recruits for clients across North America — we post representative roles like this so candidates can raise their hand before we have a specific mandate. Apply today and we'll reach out the next time a job like this comes up.

The world of work is changing faster than ever before — but the truth is, technology doesn't transform companies. People do. We build long-term relationships with the leaders driving that change across every industry vertical.

Visit our website to learn more about our process and to find free tools to support your job search — including our live job market dashboard with salary, skills, and hiring-trend data from thousands of AI transformation roles.

What the market looks like

VP, AI & Data roles are distributed across technology, professional services, financial services, and manufacturing — with particular concentration in California, New York, and Texas. Over the last six months, we've tracked 5,600+ executive-level postings in this category across the US. Compensation for this seniority typically lands in the $230k–$460k range, with strong candidates bringing both technical depth in machine learning systems and proven experience scaling AI teams and infrastructure. The best leaders in this space combine hands-on architecture skills with the ability to translate AI strategy into measurable business outcomes and to operate across business, product, and engineering stakeholders.

Typical job responsibilities

Own the vision and roadmap for AI and data capabilities, aligning with broader business strategy and market opportunity
Build and lead a team of machine learning engineers, data scientists, and analytics engineers; define hiring strategy, skill development, and performance standards
Drive architecture and infrastructure decisions for ML platforms, data pipelines, and model serving systems; own decisions on make-versus-buy and technology selection
Partner with product and business leadership to identify high-impact AI applications and translate them into technical requirements and delivery milestones
Establish governance, quality, and responsible-AI standards for models in production; drive model monitoring, validation, and retraining processes
Manage budget allocation, vendor relationships, and cloud infrastructure costs for the AI and data function
Communicate progress, wins, and risks to executive stakeholders; build business cases for AI investments and demonstrate ROI

Typical candidate requirements

10+ years in machine learning, data engineering, or analytics — with at least 3+ years in a leadership role managing technical teams
Hands-on experience designing and shipping ML systems end-to-end, including model development, evaluation, deployment, and monitoring
Track record scaling data and AI teams; experience recruiting, mentoring, and retaining technical talent
Fluency in modern data stack tools and cloud platforms (AWS, GCP, Azure); comfort making infrastructure and tooling tradeoffs
Demonstrated ability to communicate complex technical work to non-technical audiences and to align AI strategy with business priorities
Experience operating in regulated or high-stakes environments (financial services, healthcare, or enterprise software preferred)