Workday
Principal/Senior AI Engineer - Agent Factory
$206K–$370K
USA, CA, Pleasanton · Flex · Principal · Full-time · Posted Oct 20, 2026
- Experience
- P5: 10+ years software engineering plus 2+ years building production-grade LLM/agentic systems, or 7+ years in Machine Learning Engineering or AI application development plus 3+ years shipping LLM-backed products. P4: 8+ years software engineering plus 1+ year building production-grade LLM/agentic systems, or 5+ years in Machine Learning Engineering or AI application development plus 2+ years shipping LLM-backed products. Additional level-specific requirements are stated in the posting.
- Education
- Bachelor’s degree in Computer Science, Software Engineering, or equivalent technical field; Master’s preferred.
About the job
Designs and delivers production-grade AI agents, integrating models and agentic workflows into Workday products while ensuring safe, reliable performance at enterprise scale.
What you'll do
- Lead system design, implementation, and product integration for an intelligent-agent domain.
- Build and optimize AI orchestration, including agent workflows, routing, and retrieval pipelines.
- Implement responsible-AI safeguards and address latency, cost, reliability, privacy, and explainability.
What they ask for
- Meet one of the stated experience paths for the selected level: P5 or P4, including the specified LLM/agent product experience.
- Hands-on experience integrating large models and modern AI APIs into user-facing enterprise products.
- Experience designing and scaling AI orchestration architectures and optimizing application performance, including modern LLM constraints.
- Experience using cloud platforms to deploy scalable systems; strong knowledge of responsible-AI governance, guardrails, security, and evaluation.
Nice to have
- Master’s degree.
Pay
$246,000 USD - $370,000 USD (base salary); $206,000 USD - $370,000 USD (base salary)
Tools
LLMs, Foundation Models, modern AI APIs, multi-agent frameworks, routing layers, RAG, AWS, GCP
AI focus
Develop and integrate LLM-powered agents and orchestration into enterprise products, with responsible-AI governance, guardrails, and evaluation.
Model-written summary · the original posting is authoritative