Senior AI Engineer/AI Engineer III

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

As an AI Engineer/Sr. AI Engineer in Agent Factory, you will drive the end-to-end system design, implementation, and product integration for a core domain of Workday’s next generation of intelligent agents. While our ML Engineers focus on building, training, and optimizing foundational algorithms, your mission is intelligence orchestration and product delivery—connecting the brain to the product.

Sitting at the intersection of AI capabilities, enterprise platforms, and human workflows, you will develop and integrate foundational models safely and reliably into functional, production-grade software. You will be hands-on in the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into scalable business value. Because these agents interact with sensitive HR and financial data at a global scale, you will be a key contributor to Responsible and Governed AI—implementing strict guardrails for data privacy, predictability, and explainability within your pod. This role requires a balance of domain-level system architecture and rigorous execution, solving critical product constraints like latency, cost, and reliability.

About You

Basic Qualifications

• 5+ years of professional software engineering experience, with a solid track record of developing, testing, and deploying production code.
• 1+ years of professional experience (or a strong, demonstrable portfolio of applied project work) working with Large Language Models (LLMs), foundational models, or modern AI APIs.
• Demonstrated experience working with AI orchestration concepts (e.g., LangChain, LlamaIndex, or similar tooling) and a strong foundation in prompt engineering to build functional LLM-powered features.
• 2+ years of hands-on experience with API integration, backend application development, and managing data pipelines.
• 2+ years of experience working with core development languages (such as Python) and handling modern software engineering workflows (CI/CD, testing frameworks, and version control).

Basic Qualifications

• 8+ years of professional software engineering experience with strong expertise in backend architecture, distributed systems, and API design, plus 1+ years of dedicated focus building production-grade LLM/agentic systems OR 5+ years of experience specifically within Machine Learning Engineering or AI application development, with 2+ 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.
• 1+ years of experience designing and scaling AI orchestration architectures—including multi-agent frameworks, routing layers, or advanced RAG pipelines.
• 4+ years of experience optimizing application performance (specifically tackling constraints like API latency and user interaction design), with 1+ years applied to modern LLM constraints (such as token management, cost optimization, and context-window efficiency).
• 4+ years of proven experience leveraging cloud computing platforms (e.g., AWS, GCP) to deploy highly responsive, scalable systems.

Other Qualifications

• Bachelor’s degree (Master’s preferred) in Computer Science, Software Engineering, or equivalent technical field.
• Responsible AI Implementation: Strong understanding of how to execute governance, guardrails, security layers, and evaluation mechanisms necessary when deploying autonomous agents over sensitive enterprise HR and financial data.
• Technical Leadership & Mentorship: Proven track record of technically leading engineering workstreams within a pod, taking ownership of the development lifecycle, and mentoring junior-to-mid level engineers.
• Product-First AI Mindset: Deep focus on business value, user experience, and applying deep learning/large models directly to solve practical end-user challenges.
• System Design & Reusability: Proven ability to architect robust application layers that wrap around AI models, establishing reusable patterns for system predictability, error handling, and seamless UX integration.
• Experimentation & Evaluation: Skilled in rapid prototyping, benchmarking model outputs against product requirements, and setting up automated evaluation metrics (e.g., assessing retrieval quality and agentic behavior).
• Thrives in Ambiguity: Highly autonomous builder capable of taking open-ended product goals and breaking them down into concrete, scalable engineering realities.

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. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.

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