Principal AI Engineer

Workday Workday · Enterprise · Pleasanton, CA +6

Principal AI Engineer to lead end-to-end system design, architectural framework, and product integration of Workday's next generation of intelligent agents. Focus on intelligence orchestration and product delivery, integrating foundational models safely and reliably into functional, production-grade software. Architect complex agentic workflows and ensure responsible AI practices for sensitive HR and financial data.

What you'd actually do

  1. lead the end-to-end system design, architectural framework, and product integration of Workday’s next generation of intelligent agents
  2. own the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value
  3. architect how foundational models are safely and reliably integrated into functional, production-grade software
  4. architect systems with strict guardrails for data privacy, predictability, and explainability
  5. solving critical product constraints like latency, cost, and reliability

Skills

Required

  • deep expertise in distributed systems, cloud computing, and API design
  • building production-grade LLM/agentic systems
  • integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products
  • designing and scaling complex AI orchestration architectures
  • multi-agent frameworks
  • routing layers
  • advanced RAG pipelines
  • optimizing application performance
  • tackling constraints like API latency
  • user interaction design
  • modern LLM constraints (token management, cost optimization, context-window efficiency)
  • leveraging cloud computing platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems
  • Responsible AI Stewardship
  • implement governance, guardrails, security layers, and evaluation mechanisms
  • deploying autonomous agents over sensitive enterprise HR and financial data
  • technically leading cross-functional pods
  • mentoring senior engineers
  • Product-First AI Mindset
  • System Design & Integration
  • architect robust application layers that wrap around AI models
  • ensuring system predictability, error handling, and seamless UX integration
  • Experimentation & Evaluation
  • rapid prototyping
  • benchmarking model outputs against product requirements
  • managing continuous experimentation cycles for agentic behavior
  • Highly autonomous leader
  • taking complex, open-ended product goals and turning them into scalable, concrete engineering realities

Nice to have

  • Master’s degree in Computer Science, Software Engineering, or equivalent technical field
  • experience with AI safety filtering
  • experience with explainability

What the JD emphasized

  • production-grade LLM/agentic systems
  • shipping LLM-backed products
  • integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products
  • designing and scaling complex AI orchestration architectures—including multi-agent frameworks, routing layers, and advanced RAG pipelines
  • optimizing application performance (specifically tackling constraints like API latency and user interaction design), with 2+ years applied to modern LLM constraints (such as token management, cost optimization, and context-window efficiency)
  • Responsible AI Stewardship
  • architecting systems with strict guardrails for data privacy, predictability, and explainability
  • technically leading cross-functional pods
  • steering the product development lifecycle from abstract concept to successful deployment
  • Product-First AI Mindset
  • System Design & Integration
  • Experimentation & Evaluation

Other signals

  • production-grade AI
  • intelligent agents
  • global scale
  • enterprise-grade business value
  • Responsible and Governed AI