Principal/Senior AI Engineer - Agent Factory

Workday • Pleasanton, CA

3d • $206,000 - $370,000 • Hybrid

About The Position

As an AI Engineer in Workday’s Agent Factory, you will drive end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents. The role focuses on intelligence orchestration and product delivery, connecting AI capabilities to Workday products. You will develop and integrate foundational models safely and reliably into production-grade software, design and orchestrate complex agentic workflows, and translate AI capabilities into scalable business value.

You will work at the intersection of AI, enterprise platforms, and human workflows, building agents that interact with sensitive HR and financial data at global scale. You will contribute to responsible and governed AI by implementing safeguards for data privacy, predictability, and explainability. The position combines domain-level system architecture with hands-on execution, while addressing constraints such as latency, cost, and reliability.

Agent Factory consists of small, senior, cross-functional 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 and collaborate to solve customer challenges at global scale.

Requirements

• For the P5 Principal AI Engineer level: 10+ years of professional software engineering experience with deep expertise in distributed systems, cloud computing, and API design, plus 2+ years building production-grade LLM or agentic systems; alternatively, 7+ years in Machine Learning Engineering or AI application development, including 3+ years shipping LLM-backed products.
• For the P4 Senior AI Engineer level: 8+ years of professional software engineering experience with strong expertise in backend architecture, distributed systems, and API design, plus 1+ years building production-grade LLM or agentic systems; alternatively, 5+ years in Machine Learning Engineering or AI application development, including 2+ years shipping LLM-backed products.
• Hands-on experience integrating large models, including LLMs or foundation models, and modern AI APIs into user-facing enterprise products: 3+ years for P5 or 2+ years for P4.
• Experience designing and scaling AI orchestration architectures, including multi-agent frameworks, routing layers, or advanced RAG pipelines: 2+ years for P5 or 1+ years for P4.
• Experience optimizing application performance, including API latency and user interaction design, and applying optimizations to LLM constraints such as token management, cost optimization, and context-window efficiency: 6+ years overall and 2+ years with LLM constraints for P5; 4+ years overall and 1+ years with LLM constraints for P4.
• Experience using cloud computing platforms such as AWS or GCP to deploy responsive, scalable systems: 6+ years for P5 or 4+ years for P4.
• Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field.
• Strong understanding of governance, guardrails, security layers, and evaluation mechanisms for deploying autonomous agents over sensitive enterprise HR and financial data.
• Proven ability to technically lead engineering workstreams, take ownership of the development lifecycle, and mentor junior-to-mid level engineers.
• Deep focus on business value, user experience, and applying deep learning or 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 establishing automated evaluation metrics.
• Ability to work autonomously in ambiguous situations and turn open-ended product goals into scalable engineering solutions.

Nice To Haves

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

Responsibilities

• Drive end-to-end system design, implementation, and product integration for a core domain of intelligent agents.
• Connect AI capabilities to Workday products through intelligence orchestration and product delivery.
• Develop and integrate foundational models safely and reliably into functional, production-grade software.
• Design, experiment with, and orchestrate complex agentic workflows.
• Implement responsible AI safeguards for data privacy, predictability, and explainability.
• Address product constraints including latency, cost, and reliability.
• Technically lead engineering workstreams within a pod, own development lifecycle work, 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 or bonus.
• May be eligible for annual refresh stock grants.
• Flexible work arrangements, including remote work and in-person time.

What This Job Offers

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