Senior AI Engineer – Intelligence Orchestration

Job Description

Senior AI Engineer | Workday

The Tone:
This is a full-time role at Workday, located in Pleasanton, CA (hybrid) with other US remote options. Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents, shaping the future of work by building intelligent agents. This role is crucial for developing production-grade AI deeply embedded into Workday’s platform, not research experiments or maintenance work. The culture is rooted in integrity, empathy, and shared enthusiasm, where curiosity and courageous collaboration are valued.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid Pleasanton, with US remote options
• Pay: $176000–$312000 yearly
• Team: Agent Factory, forming small, senior, cross-functional AI teams with product leaders, AI engineers, and full-stack builders.
• Mission: Drive the end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents, focusing on intelligence orchestration and product delivery.
• Tech Stack: AWS, GCP

What You’ll Actually Do
• System Design & Integration: Drive the end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents.
• Intelligence Orchestration: Develop and integrate foundational models safely and reliably into functional, production-grade software, orchestrating complex agentic workflows.
• Responsible AI Implementation: Be a key contributor to Responsible and Governed AI, implementing strict guardrails for data privacy, predictability, and explainability within your pod.
• Performance Optimization: Balance domain-level system architecture with rigorous execution, solving critical product constraints like latency, cost, and reliability.
• Scalable Business Value: Translate cutting-edge AI capabilities into scalable business value, specifically designing agents that interact with sensitive HR and financial data at a global scale.

The Must-Haves
• Background: Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field, with a focus on Senior-level AI/backend software engineering.
• Experience: 8+ years of professional software engineering experience with strong expertise in backend architecture, distributed systems, and API design, including 1+ year building production-grade LLM/agentic systems. Alternatively, 5+ years in Machine Learning Engineering or AI application development with 2+ years shipping LLM-backed products. Required experience also includes 2+ years integrating large models (LLMs, Foundation Models) and modern AI APIs into user-facing enterprise products, 1+ year designing AI orchestration architectures, 4+ years optimizing application performance (including 1+ year for LLM constraints), and 4+ years deploying highly responsive, scalable systems using cloud platforms like AWS or GCP.
• Skills: Strong understanding of how to execute governance, guardrails, security layers, and evaluation mechanisms necessary when deploying autonomous agents over sensitive enterprise data; proven ability to architect robust application layers around AI models for system predictability, error handling, and seamless UX integration; demonstrated technical leadership in engineering workstreams and mentorship; skilled in rapid prototyping, benchmarking model outputs, and setting up automated evaluation metrics; deep focus on business value, user experience, and applying deep learning/large models directly to solve practical end-user challenges.
• Bonus: Master’s degree in Computer Science, Software Engineering, or an equivalent technical field.