Director of Engineering, IAEF

This executive engineering role leads the architecture, delivery, security, and growth of an AI evaluation platform focused on trustworthy AI.
You’ll shape the technical foundation for evaluating AI efficacy, transparency, safety, and reliability in educational contexts.
The position combines hands-on technical leadership with team building, platform strategy, operational excellence, and external representation.
You’ll lead a distributed engineering organization while working closely with executive, evaluation science, security, and external stakeholders.
The role offers significant ownership over platform architecture, evaluation workflows, developer ecosystems, and engineering practices.
You’ll also contribute to fundraising, partner engagement, technical due diligence, and the responsible expansion of AI evaluation capabilities.
This is a remote-first opportunity with approximately 15% travel and a preference for candidates able to participate in quarterly in-person meetings.

The ideal candidate brings deep software engineering expertise, senior technical leadership experience, and a strong understanding of distributed engineering, AI evaluation, platform architecture, security, and organizational development.

• 12+ years of software engineering experience, including at least 4 years in senior technical leadership within a startup, evaluation or audit firm, machine-learning infrastructure company, or research-grade platform team.
• Experience building and operating platforms with plugin, extension, or component models.
• Production experience with AI evaluation, red-teaming, machine-learning observability, model testing, or related systems.
• Proven ability to hire, develop, and retain senior engineers within a distributed organization.
• Experience building or leading teams that include applied machine-learning or agentic-systems expertise.
• Ability to design reusable platform components and work with human-in-the-loop transcripts, benchmark scores, and LLM red-teaming results.
• Strong understanding of platform architecture, engineering delivery, operational reliability, and technical decision-making.
• Ability to communicate complex technical decisions clearly to enterprise security leaders, foundation program officers, investors, customers, partners, and other non-technical stakeholders.
• Strong prioritization skills and the ability to balance competing technical, organizational, and delivery requirements.
• Ability to independently lead distributed engineering teams through delivery, operational challenges, and periods of growth.
• Understanding of the operational separation required between public-benefit organizations, nonprofit entities, and grant-funded programs.
• Strongly preferred experience implementing ISO 42001, the NIST AI Risk Management Framework, or SOC 2 requirements.
• Prior CTO, VP Engineering, or founding-engineer experience at an early-stage company with institutional funding is preferred.
• Experience enabling external developers to build on a platform is preferred.
• Experience developing evaluation methodologies with academic or civil-society partners is a plus.
• Experience working with enterprise security, compliance, vendor risk, or AI governance programs is valuable.
• A PhD or prior experience at a frontier AI research laboratory is not required.
• Strong communication, judgment, collaboration, and team-development skills.