Senior AI Engineer

Workday • Pleasanton, CA

1d • Hybrid

About The Position

The Senior AI Engineer will drive end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents within Agent Factory. The role focuses on intelligence orchestration and product delivery, connecting AI capabilities to Workday products. The engineer will develop and integrate foundational models safely and reliably into functional, production-grade software, and design, experiment with, and orchestrate complex agentic workflows that translate AI capabilities into scalable business value. Because the agents interact with sensitive HR and financial data at global scale, the role contributes to Responsible and Governed AI by implementing guardrails for privacy, predictability, and explainability. The work balances domain-level system architecture with execution, while addressing latency, cost, and reliability constraints.

Agent Factory consists of small, senior, cross-functional AI teams that bring together product leaders, AI engineers, and full-stack builders to create intelligent agents embedded in Workday’s platform. Teams own problems end to end, collaborate across disciplines, and build production-grade systems for customer challenges at global scale. Workday’s Flex Work approach combines in-person and remote work: employees spend at least half of their time each quarter in the office or in the field with customers, prospects, and partners, depending on the role. The position is based primarily in Pleasanton, California, with additional U.S. locations listed.

Requirements

• At least 8 years of professional software engineering experience, with strong expertise in backend architecture, distributed systems, and API design, plus at least 1 year focused on building production-grade LLM or agentic systems; alternatively, at least 5 years in Machine Learning Engineering or AI application development, including at least 2 years shipping LLM-backed products.
• At least 2 years of hands-on experience integrating large models (LLMs or foundation models) and modern AI APIs into user-facing enterprise products.
• At least 1 year of experience designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, or advanced RAG pipelines.
• At least 4 years of experience optimizing application performance, including API latency and user interaction design, with at least 1 year applying this to modern LLM constraints such as token management, cost optimization, and context-window efficiency.
• At least 4 years of experience using cloud computing platforms such as AWS or GCP to deploy responsive, scalable systems.
• Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field.
• Strong understanding of responsible AI governance, guardrails, security layers, and evaluation mechanisms for deploying autonomous agents over sensitive enterprise HR and financial data.
• Proven track record of technically leading engineering workstreams, owning development lifecycles, and mentoring junior-to-mid-level engineers.
• Product-first focus on business value and user experience, with the ability to apply deep learning and large models to practical end-user challenges.
• Ability to architect robust application layers around AI models, creating reusable patterns for predictability, error handling, and seamless UX integration.
• Skill in rapid prototyping, benchmarking model outputs, and setting up automated evaluation metrics, including retrieval quality and agentic behavior.
• Ability to work autonomously in ambiguity and translate open-ended product goals into concrete, scalable engineering solutions.

Nice To Haves

• Master’s degree in Computer Science, Software Engineering, or an equivalent technical field is preferred.

Responsibilities

• Drive end-to-end system design, implementation, and product integration for a core domain of intelligent agents.
• Develop and integrate foundational models into safe, reliable, production-grade software.
• Design, experiment with, and orchestrate complex agentic workflows.
• Implement guardrails for data privacy, predictability, and explainability for agents handling sensitive HR and financial data.
• Address product constraints including latency, cost, and reliability.
• Technically lead engineering workstreams within a pod, own the development lifecycle, and mentor junior-to-mid-level engineers.
• Prototype and benchmark model outputs against product requirements and establish automated evaluation metrics.

Benefits

• May be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
• May be eligible for annual refresh stock grants.
• Workday provides a comprehensive benefits package; details are available through Workday.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior