Principal Software Development Engineer - AI Platform

Your work days are brighter here. 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.

Do you want to build impactful, AI features and solutions that will be used by millions of end-users? We are in the AI Platform organization at Workday and we solve meaningful problems that lie at the intersection of machine learning and enterprise-scale software! We build advanced AI solutions that power the core Workday software by modeling user behavior and providing intelligent automation.

Come join us and make easier and balanced for millions of Workday users!

As a Principal Software Development Engineer for Machine Learning, you will be a team leader, working closely with other engineers and ML researchers to build and deploy robust, scalable AI platforms. You will play a vital role in turning innovative ML concepts into production-ready solutions, with a focus on agentic AI capabilities such as planning, reasoning, and action execution frameworks.

• Implement AI Platforms:
  Design and maintain sophisticated AI platform capabilities, focusing on patterns like tool calling, multi-agent architectures, and human-in-the-loop integrations. You will write clean, performant code that ensures these systems are resilient in production.
• Build ML Infrastructure:
  Develop and deploy secure, RESTful web services using Python and Kubernetes. You will contribute to the development of multi-tenant runtime architectures that enable fast inference and scale to millions of users.
• Collaborative Engineering:
  Participate in design reviews and code quality initiatives. You will apply software development best practices to ensure our codebase remains maintainable, testable, and efficient.

• Translate Requirements:
  Work with cross-functional teams to turn product requirements into functional technical designs.
• Apply MLOps Standards:
  Utilize industry-standard practices, including automation, observability, and CI/CD, to deliver high-quality ML solutions.
• Continuous Learning:
  Stay current with evolving AI/ML technologies and contribute to the team's collective knowledge.

• 8+ years experience in software development engineering including designing, developing, and deploying software solutions.
• 5+ years of experience in Python, with a consistent track record of shipping production code and systems.
• 5+ of experience building scalable data pipelines and working with large-scale datasets.
• 5+ years of validated experience deploying production services to cloud platforms (e.g., AWS, Azure, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps.
• Bachelor's degree in a relevant field such as Computer Science, Engineering, or a related discipline, or equivalent practical experience.

• Solid ability in Algorithmic Thinking to design and implement efficient solutions for agentic system development.
• Expertise in the engineering, deployment, and MLOps of advanced machine learning solutions (e.g., generative models, LLMs, RAG, and AI agents), coupled with a strong understanding of scalable distributed systems, performance optimization, database technologies (e.g., PostgreSQL, Redis), and robust API development.
• Validated algorithmic thinking and a track proven history designing, implementing, and analyzing efficient algorithms for complex problems.
• Demonstrated ability to build flexible, reusable,…