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United States
Remote only
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.
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 stabilization, while maintaining technical governance over architecture, security, integrations, model and platform changes, evaluations, monitoring, and production readiness.
Cross-Functional Operating Model: Establish clear operating interfaces, decision rights, design authorities, service expectations, escalation paths, and lifecycle responsibilities across AI Innovation, Workday and People Technology, People Data and Analytics, experience platforms, functional teams, the Execution COE, and enterprise partners.
Workday and Enterprise Collaboration: Coordinate with Workday leadership when solutions involve Workday data, processes, roles, integrations, or transactions, ensuring Workday remains the authoritative system of record.
Organizational Education and Innovation: Support discovery, intake, prioritization, portfolio governance, demonstrations, and reusable examples that help business leaders understand AI capabilities and opportunities.
Team Leadership and Talent Development: Build and lead a high-performing AI product and engineering team, setting clear expectations and accountability. Coach team members, support differentiated development and stretch assignments, build succession capability, and hire for skill gaps across architecture, engineering, security, evaluation, responsible AI, and production delivery.
External Partner Management: Use external partners selectively while retaining internal technical authority, knowledge, accountability, and ownership.
Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field, or equivalent relevant experience.
10+ years of progressive experience in technology, software, data, or AI, including leadership of enterprise-grade production solutions and teams.
3+ years of deep hands-on experience designing and delivering AI products, agents, grounded solutions, workflows, integrations, and enterprise applications in production.
Strong technical expertise in solution architecture, APIs, data flows, identity management, roles and access, security, monitoring, evaluations, and production readiness.
Experience developing AI technical strategies, architecture roadmaps, reusable technical patterns, and engineering frameworks.
Experience with enterprise AI platforms such as Microsoft Copilot, UnifyApps, Leena AI, Claude, or comparable technologies.
Demonstrated ability to embed security, privacy, responsible AI, human oversight, and auditability throughout the product lifecycle.
Strong product judgment and the ability to translate ambiguous business challenges into practical technical solutions with measurable outcomes.
Ability to remain hands-on by prototyping, reviewing technical designs and engineering work, troubleshooting complex issues, and collaborating directly with engineers.
Experience defining decision rights and operating interfaces across business, product, platform, data, portfolio, and control teams.
Proven talent leadership, including coaching, development planning, succession planning, hiring, team building, and effective use of external partners.
Preferred qualifications:
Advanced degree in Computer Science, Engineering, AI, Data Science, or a related field.
Experience building AI products outside traditional HR or People Technology environments.
Familiarity with enterprise copilots, agentic workflows, retrieval-augmented generation (RAG), orchestration platforms, and model evaluation.
Experience working in highly regulated or data-sensitive environments.
Familiarity with People processes or People technology is helpful but not required.
Annual salary range: USD $122,400–$204,400, depending on experience, qualifications, and work location.
Employment type: Full-time.
Work arrangement: Remote within the United States.
Additional benefits: U.S. benefits information is available through the employer’s benefits resources; specific benefit details are not provided in the job posting.
Company culture: An environment emphasizing innovation, service, collaboration, and professional growth.
