Overview
AI Leadership covers the executives, CTOs, heads of function, and engineering managers who set AI strategy, build and scale high-performing teams, and translate AI capability into business impact. These are the connectors between the technical teams building AI and the business leaders deploying it.
Roles We Place
- Head of AI
- VP of AI/Engineering
- CTO
- CIO
- CDO
- Chief AI Officer
- Engineering Managers (ML/Data)
- AI Product Managers
- Technical Program Managers
What We Assess
Strategic vision, team-building track record, technical depth vs breadth, stakeholder management, AI maturity assessment, budget/P&L experience
Typical Hiring Scenarios
Hiring a Head of AI to build the function from zero for an ASX-listed company — You've identified AI as a strategic priority. You need a Head of AI who combines technical credibility (understands the difference between an ML Engineer and a Research Scientist), business acumen (can articulate ROI and manage stakeholders), and team-building skills (can hire and scale a function from scratch).
Recruiting a VP of Engineering to scale a 5-person ML team to 30 — You've proved the concept. Now you need VP-level leadership who can recruit, structure, mentor, and scale engineering teams without micromanaging. This is someone who's done it before and understands AI talent markets.
Executive search for a Chief AI Officer reporting to the board — You're positioning AI as a core competitive advantage. You need a Chief AI Officer with C-level experience, board exposure, and the ability to set AI strategy while managing executive stakeholder relationships across product, engineering, finance, and legal.