Principal AI Engineer

About the role

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. Your mission is to orchestrate and deliver intelligence, connecting the brain to the product. 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.

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—architecting systems with 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.

Responsibilities

• Lead the end-to-end system design, architectural framework, and product integration of Workday’s next generation of intelligent agents.
• 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 that the systems you design adhere to strict guardrails for data privacy, predictability, and explainability.
• Solve 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.
• 2+ 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 background in distributed systems, cloud computing, and API design.
• Experience integrating large models (LLMs, Foundation Models) and modern AI APIs into enterprise products.
• Hands-on experience designing and scaling complex AI orchestration architectures.
• Proven track record of optimizing application performance, especially for modern LLM constraints.
• Experience leveraging cloud computing platforms for deployment of scalable systems.
• Deep understanding of responsible AI stewardship, including governance, guardrails, security layers, and evaluation mechanisms.
• Expertise in architecting robust application layers that wrap around AI models, ensuring system predictability, error handling, and seamless UX integration.
• Ability to rapidly prototype, benchmark model outputs, and manage continuous experimentation cycles for agentic behavior.
• Autonomous leadership with the capability to turn complex, open-ended product goals into scalable, concrete engineering realities.

Benefits

• Flexible work arrangements, spending at least half of your time each quarter in the office or in the field with our customers, prospects, and partners.
• Comprehensive benefits package, including health insurance, retirement plans, and paid time off.
• Opportunities for professional growth and development, including access to training programs and mentorship opportunities.
• Workplace culture focused on collaboration, innovation, and inclusivity.

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. Recruiters can share more detail during the hiring process.

Schedule

Our approach 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).