This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Director, People AI Engineering & Innovation based in the United States.
The Director, People AI Engineering & Innovation will lead the technical strategy, architecture, and delivery of AI solutions across the People organization. This senior, hands‑on role combines AI engineering expertise, product leadership, and organizational innovation to transform how people‑related services and processes operate. You will turn business priorities into secure, scalable, production‑ready AI products with measurable value. Working closely with executive sponsors, People teams, technology leaders, and enterprise partners, you will guide solutions from discovery through implementation and stabilization. You will establish technical standards, governance frameworks, and responsible AI practices while maintaining strong security and privacy controls. The role also offers the opportunity to build and develop a high‑performing AI engineering team and shape the future of enterprise AI adoption.
Accountabilities
- AI Strategy and Technical Roadmap: Define and evolve the People organization’s AI strategy, architecture, platform direction, and capability roadmap, translating business priorities and emerging technologies into actionable plans.
- Engineering Standards and Delivery Framework: Establish reusable technical patterns, engineering standards, decision frameworks, and delivery practices to move AI solutions from concept to production, stabilization, and formal ownership transfer.
- Opportunity Assessment and Solution Selection: Partner with executive sponsors, People teams, and the Execution COE to assess business opportunities, determine technical feasibility, and evaluate whether AI, Workday, automation, process simplification, or another platform is the most appropriate solution.
- Hands‑On AI Engineering: Serve as the technical authority for People AI solutions across approved platforms, participating directly in discovery, prototyping, architecture design, workflow and integration design, technical reviews, evaluations, and troubleshooting.
- End-to-End Product Delivery: Lead approved AI solutions through discovery, design, development, validation, launch, and stabilization. Establish grounded‑solution approaches, evaluation methods, documentation, and reusable engineering practices.
- Security, Privacy, and Responsible AI: Integrate security, privacy, identity, access controls, least‑privilege permissions, and People‑data protection throughout the AI product lifecycle. Partner with IT, Infrastructure, Information Security, Privacy, Legal, and enterprise AI governance teams.
- Governance and Risk Management: Ensure appropriate human oversight, escalation procedures, monitoring, auditability, and controls for sensitive or higher‑risk use cases. Retain authority over architecture, security, access, integrations, model changes, and production readiness, and pause changes that do not meet required standards.
- Value Measurement and Lifecycle Management: Define success metrics covering adoption, quality, capacity released, user experience, control effectiveness, and return on investment. Partner with product owners and the Execution COE to review results and recommend whether solutions should scale, improve, remain unchanged, or be retired.
- Ownership and Technical Governance: Complete formal transfers to designated business or product owners following