Director of Engineering, IAEF

Accountabilities: The Director of Engineering will own the technical direction and execution of the platform while building a high-performing engineering organization, strengthening security and compliance practices, and representing the technical vision to external stakeholders.

• Own the Workbench’s Design → Test → Analyze → Publish (DTAP) workflow, Component Contract, Artifacts API, component registry, and canvas interface.

• Build a persistent, structured, and queryable evaluation history while integrating existing red-teaming, administrative dashboard, and human-in-the-loop data-capture capabilities.

• Evaluate build-versus-buy decisions for authentication, storage, orchestration, LLM-provider services, sandboxing, and other core platform capabilities.

• Recruit, develop, and retain the engineering organization in partnership with the HR function, including Staff/Senior Backend, Senior Frontend, DevOps/Site Reliability, Applied Machine Learning, and Senior Product Management roles.

• Establish effective planning, code review, on-call, incident response, and roadmap review practices.

• Track engineering progress, risks, and delivery outcomes for board and funder reporting.

• Partner with the CEO and Evaluation Science Lead to translate human-in-the-loop red teaming, automated benchmarks, LLM red teaming, LLM-as-judge, and drift detection into a reusable Component Contract.

• Ensure the platform supports the required Test artifact types and planned agentic components.

• Lead vendor risk reviews covering LLM providers, cloud infrastructure, and third-party evaluation tools.

• Coordinate with organizational leadership on required approvals, funder restrictions, and the appropriate separation of resources, data, and intellectual property across related entities and funded programs.

• Escalate unresolved legal, policy, or sponsor-related risks through the appropriate leadership channels.

• Represent the platform in technical discussions with customers, partners, funders, and press.

• Own technical content for investor fundraising materials, roadmaps, demonstrations, and due diligence reviews in collaboration with executive leadership.

• Shape the developer-relations narrative for SDK and ADK capabilities as the Component Contract becomes available to external developers.

• Partner with planned Developer Relations and Ecosystem leadership to support external developer adoption.

• Provide technical leadership across delivery, operational issues, organizational growth, and continuous platform improvement.

Requirements:

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.

Benefits:

• $215,000–$315,000 annual compensation, commensurate with experience.

• Remote-first, full-time position.

• Health, dental, and vision insurance, with 100% of employee premiums and 85% of dependent premiums covered.

• $365 monthly employer contribution to a pre-tax Health Savings Account.

• Pre-tax Flexible Spending Account.

• Employer-paid AD&D insurance.

• Employer-paid short-term and long-term disability insurance.

• Employer-paid basic life insurance.

• Supplemental voluntary life insurance for employees, spouses, and dependent children.

• Pet insurance options, including Total Pet Plan and Supplemental Wishbone coverage.

• Employee Assistance Program supporting health and wellness.

• Wellness reimbursement program.

• 401(k) retirement plan with 6% employer matching.

• 15 days of paid time off annually, increasing to 20 days after the third anniversary and 25 days after the sixth anniversary.

• 16 paid holidays, including 14 common holidays and 2 flexible holidays.

• Paid bereavement leave.

• Paid parental leave for mothers and fathers, including two weeks after the first year.

• Approximately 15% travel for funder meetings, partner sites, conferences, and off-sites.

• Quarterly in-person meetings, with New York or the San Francisco Bay Area strongly preferred for proximity to key stakeholders.

• Opportunity to lead an impactful AI evaluation platform focused on trustworthiness, transparency, safety, and educational applications.

• High degree of technical ownership across architecture, engineering strategy, security, and platform growth.

• Opportunity to influence AI evaluation practices, external developer ecosystems, and responsible AI initiatives.

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