Workday – HR AI Experience and Architecture Lead
Must Have Technical/Functional Skills
• 10–15+ years of experience in HR Technology, Enterprise Applications, or Digital Platforms
• Strong expertise in:
• Workday architecture and HR processes
• Integration patterns and enterprise system design
• Hands-on experience or strong familiarity with:
• Microsoft Copilot / M365 ecosystem
• LLM-based platforms (e.g., Claude or similar)
• AI-enabled enterprise applications
• Proven ability to:
• Translate business needs into technical architecture and solutions
• Work across multiple platforms and systems
• Strong understanding of:
• APIs, integrations, and data flows
• Security and governance considerations in HR systems
Experience working in product-based or platform-based operating models
Role Summary
We are seeking a senior, technically strong HR AI Experience & Architecture Lead to define and evolve our HR Assist platform into a next-generation, AI-powered employee experience layer. This role will combine deep Workday and HR domain knowledge, strong technical architecture thinking, and AI platform expertise to help design how HR Assist connects across systems, leverages AI capabilities, and delivers a seamless, intelligent employee experience.
The individual will play a critical role in helping define:
• How HR Assist evolves beyond a chatbot into a unified HR experience platform
• How to architect connectivity across Workday, Microsoft Copilot, Claude, Dayforce, and other systems
• Which AI capabilities should be built, integrated, or leveraged from existing platforms
This is not a pure strategy role — it requires hands-on technical thinking, architecture mindset, and product leadership to translate vision into scalable solutions.
Key Responsibilities
HR Assist Platform Evolution
• Define and drive the next phase of HR Assist, transforming it from a chatbot into a central AI-powered HR experience layer
• Design how HR Assist supports:
• Employee self-service
• Manager interactions
• Case management and knowledge access
• Transactional and advisory HR journeys
• Identify gaps in current capabilities and define future-state experience vision
• ________________________________________
AI Operating Model & Platform Design
• Lead the technical thinking and framework design for how AI capabilities are delivered across HR systems
• Define how HR Assist integrates with:
• Workday (transactions, case management, knowledge, workflows)
• Microsoft Copilot (productivity, enterprise workflows, M365 ecosystem)
• Claude or similar LLM platforms (advanced reasoning, content generation, knowledge synthesis)
• Dayforce and other systems (employee-facing use cases)
• Evaluate and recommend:
• What should be built vs integrated vs leveraged
• Where each platform is best suited
• How to avoid duplication and fragmented experiences
• ________________________________________
Use Case Engineering & Solution Design
• Translate HR needs into AI-enabled use cases and technical solutions
• Lead design of:
• Intelligent workflows
• Conversational experiences
• AI-driven decision support
• Work closely with:
• Solution engineers
• Enterprise architects
• Data and integration teams
to define end-to-end solution architecture
• ________________________________________
Cross-Platform AI Strategy (Execution-Focused)
• Help operationalize the HR AI strategy and roadmap
• Define clear patterns and guardrails for:
• When to use Workday-native AI
• When to leverage Copilot
• When Claude (or similar) is more appropriate
• Ensure HR Assist acts as a cohesive front-end experience, regardless of backend platform
• ________________________________________
Technical Depth & Integration Thinking
• Drive architecture for:
• APIs and integrations
• Data flows across systems
• Real-time vs batch interactions
• Security and role-based access
• Partner with engineering teams to ensure solutions are:
• Scalable
• Maintainable
• Aligned with enterprise standards
• ________________________________________
Governance, Risk & Responsible AI
• Help define governance for:
• AI usage across HR platforms
• Sensitive HR data handling
• Model selection and usage boundaries
• Ensure solutions align with security, compliance, and ethical AI principles
• ________________________________________
Stakeholder Partnership
• Work closely with:
• HR leadership
• HR technology product teams
• Enterprise architecture
• Security and data teams
• Act as a bridge between business needs and technical execution
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