Senior Director, Context and Semantics Engineering (AI)

Workday•Pleasanton, CA

9d•$231,800 - $422,400•Hybrid

About The Position

The Data Cloud organization is at the forefront of Workday’s next major wave of innovation, driven by a bold mandate to build the industry’s first true Platform for Agents. We are a high-energy, ambitious team that balances Workday's deep foundational expertise with fresh, forward-thinking perspectives to accelerate our pace of delivery and unlock massive new commercial value. By leveraging Workday’s unique business context, trusted data, and identity guardrails, we are building the critical engine that will power the future of AI and agentic workflows across the enterprise. As a team, we value organizational clarity, deep cross-functional collaboration, and rapid execution, working together to evolve our architecture and aggressively scale our impact in the market. Join the Data Cloud organization, where we are building the intelligent foundation for Workday's next generation of AI Agents. The Context and Semantics Engineering team is the brain trust responsible for making our AI "enterprise-aware." We build the semantic layers, knowledge graphs, and dynamic context engines that ground generative AI in real-world HR and Finance data. By bridging the gap between raw enterprise data and large language models (LLMs), our team ensures that Workday’s autonomous agents can reason accurately, securely, and with deep contextual awareness at a global scale. As the Senior Director of Context and Semantics Engineering, you will be a key engineering executive driving the vision, architecture, and delivery of the intelligence layer powering Workday’s AI Agents. You will lead and scale an engineering organization to build highly scalable semantic engines, advanced RAG (Retrieval-Augmented Generation) pipelines, vector search infrastructure, and dynamic context-management systems. Sitting at the critical intersection of data architecture and applied AI, you will ensure that our foundational models seamlessly understand and reason over complex, highly regulated enterprise workflows. This is a high-visibility, high-impact role requiring a visionary leader who can scale organizations, navigate technical ambiguity, and deliver production-grade AI infrastructure that sets the industry standard for Enterprise AI.

Requirements

10+ years of progressive software engineering experience with a strong background in distributed systems, search architectures, data platforms, or AI infrastructure.
5+ years of senior engineering leadership experience (Director level or above), with a proven track record of managing managers, scaling organizations (50+ engineers), and delivering mission-critical enterprise systems.
3+ years of direct experience leading teams that build AI/ML infrastructure, semantic search engines, LLM orchestration layers, vector databases, or Knowledge Graphs.
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. is a plus).
Deep architectural understanding of how to bridge structured enterprise data with unstructured AI models (RAG architectures, embedding generation, chunking strategies, and semantic routing).
Experience building and scaling Semantic Layers, Ontologies, or enterprise-scale Search/Retrieval systems (e.g., Elasticsearch, Pinecone, Milvus, Neo4j).
Strong executive presence and communication skills, with the ability to translate complex AI and data concepts into clear business value for non-technical stakeholders.
Product-first mindset with a relentless focus on delivering high-reliability, low-latency infrastructure that powers real-time AI user experiences.
Experience operating within highly regulated data environments (Finance/HR) and implementing AI guardrails for enterprise-grade security.

Nice To Haves

Experience with the Workday platform and architecture is a strong plus.

Responsibilities

Build, scale, and mentor a world-class engineering organization dedicated to AI context, semantic architecture, and data orchestration.
Define and execute the technical roadmap for Workday’s AI semantic layer, encompassing vector databases, knowledge graphs, enterprise ontologies, and semantic search capabilities.
Lead the development of enterprise-grade RAG pipelines, ensuring LLMs are grounded in real-time, accurate, and tenant-isolated HR and Finance data to eliminate hallucinations and drive agentic reasoning.
Collaborate tightly with VP/C-level stakeholders across AI/ML Engineering, Product Management, and Platform Architecture to seamlessly integrate context engines into the broader AI Agent Factory and Sana experiences.
Drive the engineering design for agentic memory, state management, and conversational context, allowing our AI agents to seamlessly handle multi-turn, complex user workflows.
Enforce rigorous technical standards for data privacy, RBAC (Role-Based Access Control), and compliance, ensuring that context fed to AI models strictly adheres to enterprise security boundaries.
Evaluate and integrate cutting-edge AI data technologies and orchestration frameworks (e.g., advanced embedding models, GraphRAG, LlamaIndex, LangChain) to future-proof Workday's AI platform at massive scale.