Principal AI Engineer

About the role

The role involves leading the end-to-end system design, architectural framework, and product integration of Workday's next generation of intelligent agents. You will architect how foundational models are safely and reliably integrated into functional, production-grade software. You will own the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value.

These agents interact with sensitive HR and financial data at a global scale, requiring you to be a core champion for Responsible and Governed AI—architecting systems with strict guardrails for data privacy, predictability, and explainability.

Responsibilities

• Lead the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value.
• Architect how foundational models are safely and reliably integrated into functional, production-grade software.
• Own the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value.
• Ensure system predictability, error handling, and seamless UX integration.
• Optimize application performance, specifically tackling constraints like API latency and user interaction design.
• Manage continuous experimentation cycles for agentic behavior.
• Implement governance, guardrails, security layers, and evaluation mechanisms necessary when deploying autonomous agents over sensitive enterprise HR and financial data.
• Balance high-level system design and hands-on execution, solving critical product constraints like latency, cost, and reliability.

Requirements

• 10+ years of professional software engineering experience with deep expertise in distributed systems, cloud computing, and API design, plus 2+ years of dedicated focus building production-grade LLM/agentic systems OR 7+ years of experience specifically within Machine Learning Engineering or AI application development, with 3+ years dedicated to 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 of experience designing and scaling complex AI orchestration architectures—including multi-agent frameworks, routing layers, and advanced RAG pipelines.
• 6+ years of experience 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).
• 6+ years of proven experience leveraging cloud computing platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems.

Qualifications

• Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or equivalent technical field.
• Deep understanding of how to implement governance, guardrails, security layers, and evaluation mechanisms necessary when deploying autonomous agents over sensitive enterprise HR and financial data.
• Proven track record of technically leading cross-functional pods, mentoring senior engineers, and steering the product development lifecycle from abstract concept to successful deployment.
• Deep focus on business value, user experience, and applying deep learning/large models directly to solve practical end-user challenges.
• Expert-level ability to architect robust application layers that wrap around AI models, ensuring system predictability, error handling, and seamless UX integration.
• Skilled in rapid prototyping, benchmarking model outputs against product requirements, and managing continuous experimentation cycles for agentic behavior.
• Highly autonomous leader capable of taking complex, open-ended product goals and turning them into scalable, concrete engineering realities.

Skills

• Strong knowledge of distributed systems, cloud computing, and API design.
• Experience with large models (LLMs, Foundation Models) and modern AI APIs.
• Hands-on experience in designing and scaling complex AI orchestration architectures.
• Proven track record of optimizing application performance, especially in the context of modern LLMs.
• Experience with cloud computing platforms such as AWS and GCP.
• Ability to architect robust application layers that wrap around AI models.
• Expertise in rapid prototyping, benchmarking model outputs, and managing continuous experimentation cycles.
• Highly autonomous leadership and the ability to turn complex product goals into scalable engineering realities.

Benefits

Workday offers a competitive compensation package, including the annualized base salary range for the primary location and any additional locations, as well as the possibility of the Workday Bonus Plan or a role-specific commission/bonus, and annual refresh stock grants. The application deadline for this role is the same as the posting end date stated as below: 07/31/2026.

Pay

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants.

Schedule

Our approach to flexible work combines the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role).