Head of AI

What is a Head of AI?

A Head of AI owns the company's artificial intelligence strategy and execution — translating AI capabilities into product features and competitive differentiation. The role combines technical leadership (evaluating models, directing ML engineers, setting AI architecture) with business judgment (deciding where AI creates the most value, managing AI costs and risks). In 2026, the Head of AI is one of the most sought-after and least-well-defined executive roles in tech.

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At what stage should you hire a Head of AI?

Series A and beyond, for any company with AI at its core. For companies adding AI to an existing product, typically Series B when AI is strategic enough to warrant dedicated leadership beyond a senior ML engineer. The signal: AI is a board-level priority, but there's no single person accountable for the AI roadmap, AI quality, and AI infrastructure simultaneously.

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Common titles for this role

• Head of AI
• VP of AI
• Head of Machine Learning
• Chief AI Officer
• Head of Applied AI
• Director of AI/ML

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Typical background

Strong Heads of AI have shipped AI systems in production — not just published research. RFS looks for candidates from companies like Palantir, Scale AI, OpenAI, Anthropic, Google DeepMind, or top AI-native startups like Windsurf. The most effective Heads of AI combine deep ML knowledge with product intuition and the ability to build and lead a team of ML engineers.

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What does a Head of AI do at a startup?

• Define the company's AI strategy: where AI creates value, which models to use, build vs. buy decisions
• Lead the ML engineering team: hiring, technical direction, project prioritization
• Evaluate and integrate AI models and APIs (OpenAI, Anthropic, open-source LLMs)
• Own AI quality: evaluation frameworks, model benchmarking, production monitoring
• Manage AI infrastructure costs and optimize model inference
• Partner with product managers on AI feature roadmap and user experience
• Represent the company's AI capabilities externally: customers, investors, recruiting

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Key skills and qualifications

• 7+ years of ML/AI engineering experience, with production deployments at scale
• Deep knowledge of LLMs, fine-tuning, RAG architectures, and AI evaluation frameworks
• Experience managing ML engineers and building AI teams
• Strong product intuition — ability to translate AI capabilities into user value
• Familiarity with AI infrastructure: GPUs, distributed training, inference optimization
• Track record of shipping AI features that measurably improved business outcomes

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Why hire your Head of AI through RFS?

• We've placed ML engineers at Palantir, Scale AI, and Windsurf — our network reaches the best AI talent in 2026
• 29-day average time to hire — Head of AI searches are among the most competitive; our AI-native network is an advantage
• Pre-vetted for production ML experience, not just academic credentials
• 300+ placements at VC-backed companies, with growing depth in AI-native companies
• No upfront fees