• Lead the People function’s AI platform strategy, including the architectural design of AI-enabled employee and leader experiences. • Own platform selection and evaluation for the People AI assistant ecosystem (orchestration layers or agent communication protocol, RAG, agent frameworks, workflow engines). • Define the modular AI architecture required for secure integrations with Workday, ServiceNow, intranet platforms, and other data sources. • Establish standards for model usage, retrieval patterns, data access, versioning, logging, and system reliability. • Serve as the People function’s primary partner with IT, Enterprise Architecture, Cybersecurity, Legal and Risk for all AI-related technology and governance decisions. • Negotiate and align on data access patterns, authorization models, and integration pathways. • Represent the People function in enterprise-level AI forums, steering groups, and architecture reviews. • Ensure the People function’s AI strategy aligns to enterprise roadmaps while enabling innovative pilot opportunities. • Maintain the People function’s AI governance framework, including compliance standards, auditability requirements, safety guardrails, and escalation pathways. • Define guardrails for automated actions, system boundaries, fail-safes, and human-in-the-loop patterns. • Partner with Legal and Cyber to assess and mitigate risk associated with new use cases and vendor capabilities. • Establish monitoring mechanisms for reliability, performance, and ethical deployment. • Lead technical evaluation of AI vendors and platforms; establish architecture requirements for onboarding and implementation. • Partner with Digital Experience and Enablement Architecture teams to ensure platforms adhere to design, workflow, and content standards. • Define integration expectations, data flows, and technical constraints. • Oversee technical specialists and AI engineering resources supporting the platform. • Partner with Experience Architecture on workflow logic, triage patterns, decision boundaries, and human-machine interaction standards. • Support Workday/VNDLY, ServiceNow, and digital platform teams in AI-enablement opportunities, while ensuring integrity of system-of-record logic. • Provide technical guidance and architectural oversight for AI-enabled processes and cross-system workflows. • Build a multi-year AI roadmap for the People Function, including platform evolution, capability expansion, and integration milestones. • Evaluate emerging technologies, enterprise AI investments, and new architectural patterns to inform strategic decision-making. • Ensure the People function’s AI ecosystem evolves toward greater automation, personalization, and employee experience quality.

• Architecting Agentic Workflows: Design, deploy, and iterate on multi-agent systems. • Email Operations at Scale: Build and manage agent-driven email frameworks. • Content Supply Chain: Develop AI-powered pipelines. • Orchestration & Governance: Define the 'human-in-the-loop' (HITL) protocols. • Tech Stack Integration: Develop integrations between AI agents and our core toolkit. • Continuous Optimization: Establish KPIs for AI agents and refine prompts.

• Analyze existing company and consulting processes and identify areas with potential for AI deployment • Conduct market and technology research on suitable AI tools • Evaluate the identified technologies with regard to practical applicability • Prepare a structured overview of your findings and recommendations to jointly decide which tools should be adopted • Implement the agreed solutions • Test and document the new solutions

• Red-team AI models and agents by testing jailbreak attempts, prompt injections, misuse scenarios, and exploit strategies • Generate high-quality human evaluation data by annotating model failures, classifying vulnerabilities, and identifying systemic risks • Apply structured testing methodologies using taxonomies, benchmarks, and playbooks to ensure consistent evaluation • Document findings clearly and reproducibly, producing reports, datasets, and adversarial test cases that teams can act upon • Work across multiple projects, supporting different AI systems and evaluation objectives