Director of Machine Learning Engineering - Agent Factory

Workday•Seattle, WA

6h•Hybrid

About The Position

Workday is seeking a highly skilled and visionary Senior Manager or Director of AI Agent Engineering to lead the development of AI agents for their HR and Finance business. This role involves building and mentoring a high-performing engineering team, driving technical excellence, and ensuring the delivery of robust, scalable, and secure AI agent solutions that seamlessly integrate with the Workday ecosystem and deliver outstanding experiences for customers. The AI Agent Engineering team is pioneering cutting-edge HR & Finance AI Agents that deeply integrate within the Workday suite, architecting intelligent agents that will revolutionize customers' workday.

Requirements

5+ years of experience in software engineering leadership, with a strong focus on AI/ML and cloud-based systems.
5+ years of experience with design and development for mission critical systems at scale.
Proven ability to seek out and hire the highest performing professionals to build cutting edge products built on AI.
Deep understanding of LLMs, AI agents, RAG, and orchestration frameworks.
Experience with enterprise-grade AI architectures, API integration, and large-scale automation.
Strong problem-solving, communication, and collaboration skills.

Nice To Haves

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Experience with the Workday platform is a strong plus.

Responsibilities

Build, lead, and mentor a team of exceptional AI agent engineers.
Ensure timely project delivery to exceptional standards of our AI agents.
Work closely with product managers, data scientists and other stakeholders to translate business requirements into technical solutions.
Collaborate with architects and principal engineers to ensure seamless integration with the Workday platform.
Foster a culture of innovation, collaboration and continuous improvement and learning.
Evaluate and integrate cutting-edge AI technologies, including LLMs, RAG, and orchestration frameworks (e.g., LangGraph).
Collaborate with external vendors and open-source communities to leverage best-in-class AI technologies.
Ensure all AI solutions adhere to data privacy, security, and compliance standards.
Implement robust testing, monitoring and feedback loops to ensure agent performance and reliability.
Ensure the scalability, reliability, and security of AI agent solutions within the Workday environment.