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 also own the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value.

Due to the sensitivity of HR and financial data, you will 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.
• Translate cutting-edge AI capabilities into enterprise-grade business value.
• Architect systems with strict guardrails for data privacy, predictability, and explainability.

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

• Deep expertise in distributed systems, cloud computing, and API design.
• Hands-on experience integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products.
• Experience designing and scaling complex AI orchestration architectures.
• Proven experience optimizing application performance, especially for modern LLM constraints.
• Proven experience leveraging cloud computing platforms to deploy highly responsive, scalable systems.
• Deep understanding of how to implement governance, guardrails, security layers, and evaluation mechanisms for deploying autonomous agents over sensitive enterprise HR and financial data.
• Expert-level ability to architect robust application layers that wrap around AI models.
• 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.

Benefits

Our benefits package includes:

• Comprehensive health insurance options.
• Flexible spending accounts for healthcare and dependent care.
• Retirement savings plans with employer contributions.
• Employee assistance programs.
• Professional development opportunities.
• Work-life balance initiatives.

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

We combine 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).