Principal AI Engineer

Your work days are brighter here. We’re obsessed with making hard work pay off for our people, customers, and the world. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we shape the future of work so teams can reach their potential and focus on what matters most.

The minute you join, you’ll feel it, not just in the products we build but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We tackle big challenges with bold ideas and genuine care, inviting curious minds and courageous collaborators to bring optimism and drive. Whether you’re building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workday’s team.

About the Team:
Agent Factory is where Workday’s next chapter is built. We form small, senior, cross‑functional AI teams that bring together product leaders, AI engineers, and full‑stack builders to create intelligent agents used by millions every day. These are production‑grade AI systems deeply embedded in Workday’s platform, not research experiments.

As a Principal AI Engineer in Agent Factory, you will lead the end‑to‑end system design, architectural framework, and product integration of Workday’s next generation of intelligent agents. While our ML engineers focus on building, training, and optimizing foundational algorithms, your mission is intelligence orchestration and product delivery—connecting the brain to the product. You will own the design, experimentation, and orchestration of complex agentic workflows, translating cutting‑edge AI capabilities into enterprise‑grade business value.

Because these agents interact with sensitive HR and financial data at a global scale, you will be a core champion for Responsible and Governed AI, ensuring strict guardrails for data privacy, predictability, and explainability. This role requires a balance of high‑level system design and hands‑on execution, solving critical product constraints like latency, cost, and reliability.

• Architect and deploy production‑grade LLM/agentic systems that integrate with enterprise platforms and human workflows.
• Design secure, scalable, and high‑performance AI orchestration architectures for multi‑agent frameworks, routing layers, and RAG pipelines.
• Lead the responsible AI strategy, establishing guardrails for data privacy, predictability, and explainability in autonomous agent deployment.
• Collaborate with cross‑functional teams to translate business requirements into AI‑enabled products that meet global customer needs.
• Oversee end‑to‑end delivery, ensuring system reliability, cost‐efficiency, and low latency at scale.
• Mentor senior engineers and drive the product development lifecycle from concept to deployment.

• 10+ years of professional software engineering experience with deep expertise in distributed systems, cloud computing, and API design, plus 2+ years focused on production‑grade LLM/agentic systems, OR 7+ years of experience specifically within Machine Learning Engineering or AI application development, with 3+ years shipping LLM‑backed products.
• 3+ years of hands‑on experience integrating large models (LLMs, Foundation Models) and modern AI APIs into user‑facing enterprise products.
• 2+ years designing and scaling complex AI orchestration architectures—including multi‑agent frameworks, routing layers, and advanced RAG pipelines.
• 6+ years of experience optimizing application performance, with 2+ years applied to modern LLM constraints such as token management, cost optimization, and context‑window efficiency.
• 6+ years proven experience leveraging cloud platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems.
• Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or equivalent technical field.
• Deep understanding of Responsible AI governance, security layers, and evaluation mechanisms for autonomous agents handling sensitive enterprise data.
• Track record of technically leading cross‑functional pods, mentoring senior engineers, and steering product development lifecycle from…