Senior AI Engineer

Workday’s Agent Factory is building production-grade intelligent agents that are embedded into Workday’s platform and used by millions of people every day. In this Senior AI Engineer role (hybrid in Pleasanton, CA), you will lead the end-to-end design, implementation, and product integration for a core domain of Workday’s next generation of agents, with an emphasis on intelligence orchestration and responsible, governed AI integration into enterprise software.

You’ll help connect model intelligence to real product workflows by developing and integrating foundational models safely and reliably into functional, production-grade systems. The work includes hands-on design and experimentation for complex agentic workflows, along with translating advanced AI capabilities into scalable business value while meeting enterprise constraints for latency, cost, and reliability.

What you’ll do

• Drive end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents.
• Focus on intelligence orchestration and product delivery to connect the “brain” to the product experience.
• Develop and integrate foundational models safely and reliably into production-grade software.
• Be hands-on in the design, experimentation, and orchestration of complex agentic workflows.
• Translate cutting-edge AI capabilities into scalable business value.
• Implement strict guardrails for data privacy, predictability, and explainability within your pod for agents interacting with sensitive HR and financial data at global scale.
• Balance domain-level system architecture and rigorous execution to meet critical product constraints such as latency, cost, and reliability.

What you bring

• 8+ years of professional software engineering experience with strong backend architecture, distributed systems, and API design, plus either 1+ years focused on building production-grade LLM/agentic systems, or 5+ years in Machine Learning Engineering or AI application development with 2+ years dedicated to shipping LLM-backed products.
• 2+ years of hands-on experience integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products.
• 1+ years of experience designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, or advanced RAG pipelines.
• 4+ years optimizing application performance, including work on API latency and user interaction design, with 1+ years focused on modern LLM constraints such as token management, cost optimization, and context-window efficiency.
• 4+ years leveraging cloud computing platforms (AWS, GCP) to deploy responsive, scalable systems.
• Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or an equivalent technical field.
• Strong understanding of governance execution, including guardrails, security layers, and evaluation mechanisms for deploying autonomous agents over sensitive enterprise HR and financial data.
• Proven technical leadership within a pod, taking ownership across the development lifecycle and mentoring junior-to-mid level engineers.
• Deep focus on business value and user experience, applying deep learning and large models to solve practical end-user challenges.
• Proven ability to architect robust application layers around AI models for system predictability, error handling, and seamless UX integration.
• Skilled in rapid prototyping, benchmarking model outputs against product requirements, and setting up automated evaluation metrics such as retrieval quality and agentic behavior.
• Highly autonomous builder who can break open-ended product goals into concrete, scalable engineering realities.

Technologies

• AWS
• GCP
• LLMs
• Foundation Models
• Multi-agent frameworks
• Routing layers
• RAG pipelines
• AI APIs
• Cloud computing platforms

Compensation

• Primary location base pay range: $208,000 USD - $312,000 USD (USA.CA.Pleasanton)
• Additional US locations base pay range: $176,000 USD - $312,000 USD
• Eligible for the Workday Bonus Plan or a role-specific commission/bonus
• Annual refresh stock grants

About the team

• Agent Factory is where Workday’s next chapter gets built.
• Work is organized into small, senior, cross-functional AI teams with product leaders, AI engineers, and full-stack builders.
• This is production-grade AI embedded into Workday’s platform, not research experiments or maintenance work.
• Teams own problems end to end, collaborate tightly across disciplines, and build solutions for real customer challenges at global scale.

Work model

• With Flex Work, combine in-person time and remote.
• Spend at least 50% of your time each quarter in the office or in the field with customers, prospects, and partners (depending on role).
• Remote “home office” roles have the opportunity to come together in Workday offices for important moments.

Equal opportunity and candidate privacy: Workday will consider qualified applicants with arrest and conviction records under applicable fair chance law. Workday also provides reasonable accommodations during the application process and regarding the use of AI tools for employment decision-making. Workday will never ask candidates to apply through non-Workday Careers websites and will never ask candidates to pay recruiting fees or for consulting or coaching services. For reasonable accommodations, contact [email protected].