Practice 03

Technology & AI

Executive search where technology is central to product, performance, market access, data, and competitive advantage.

Technical leadership and scarce expertise.Financial technology, trading technology, AI/ML, data, infrastructure, and engineering leadership.
Technology and infrastructure environment
Focus

Technical ownership. Proven execution.

The strongest technical candidates show what they have built, scaled, and delivered, not just which technologies appear on a résumé.

Financial & Trading Technology

Technology leadership and specialists for electronic markets, trading systems, FinTech, APIs, and financial infrastructure.

AI / Machine Learning

Applied AI, ML engineering, research, model development, and AI leadership.

Data & Infrastructure

Data engineering, distributed systems, cloud, reliability, low-latency systems, and platform leadership.

Engineering Leadership

CTO, VP Engineering, architecture, platform, technical product, and senior engineering management.

Who we serve

Client environments

  • Financial-markets and FinTech firms
  • Software and data companies
  • AI-native businesses
  • Trading and market-infrastructure platforms
  • Technology-enabled investment firms
  • Enterprise technology organizations
What we hire

Representative talent

  • CTO / VP Engineering
  • AI / ML leaders and specialists
  • Data leaders and engineers
  • Platform and infrastructure leaders
  • Technical product leaders
  • Trading-technology specialists
What we assess

Evidence that matters

  • Technical depth
  • Architecture ownership
  • Team scope and leadership
  • Product / business impact
  • Scale and complexity
  • Build-vs-operate experience
  • Talent attraction
  • Compensation and timing
Hiring challenges

Look beyond the technology stack.

Architecture, operational responsibility, and business impact are central to evaluating specialist technology leadership.

Ownership

What did they build?

Distinguish direct technical ownership from project participation. Examine architecture decisions, production delivery, and measurable outcomes.

Leadership

Can they scale the team?

Evaluate hiring, organizational design, technical judgment, and delivery across engineering and business stakeholders.

Execution

Does it work in production?

For AI, data, and trading technology, assess reliability, performance, integration, operational constraints, and real-world adoption.

Client Perspective
“Quality candidates… great screening process.”
Jeff Medek · Director, IT Project Office · Navistar
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