Senior/Principal AI Engineer

Workday, Inc.

Anywhere Full-time 2026-07-06

About Workday, Inc.

Workday, Inc. is a Fortune 500 company and a leading AI platform for managing people, money, and agents. We are shaping the future of work by creating intelligent solutions that empower teams to reach their full potential. Our company culture is built on integrity, empathy, and a collective passion for innovation, supporting our employees, customers, and the world around us. We believe in trust, providing the tools for growth, skill development, and long-term investment in our Workmates.

About the Position

Introduction

Workday is seeking a Senior/Principal Machine Learning Engineer to join the Agent Factory team. We are a Fortune 500 company and a leading AI platform focused on shaping the future of work by developing intelligent agents used by millions. Our culture values integrity, empathy, and a shared enthusiasm for tackling big challenges with bold ideas and genuine care.

Responsibilities

As a Senior/Principal Machine Learning Engineer in Agent Factory, you will:

Design and build core ML systems for Workday's next-generation AI agents.
Own the full lifecycle of models, agent logic, and orchestration layers in production, from problem framing and data strategy to deployment, monitoring, and continuous improvement.
Implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops.
Ensure solutions are scalable, observable, and enterprise-ready.
Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack.
Stay hands-on with emerging techniques in agentic architectures while applying strong engineering judgment to build reliable, explainable systems at global scale.

Requirements

For P5, Principal Machine Learning/AI Engineer:

Experience: 10+ years in data science, machine learning engineering, or software development building applied machine learning products at scale (applied research, design, implementation, production, and evaluation).
ML Frameworks: 4+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow.
Production ML: 6+ years of professional experience in building services to host machine learning models in production at scale.
LLMs/GenAI: 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases.
Cloud Platforms: 6+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).
Leadership: Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.
Education: Bachelor's degree (Master's or PhD preferred) in engineering, computer science, physics, math, or equivalent.

For P4, Senior Machine Learning/AI Engineer:

Experience: 7+ years in data science, machine learning engineering, or software development building applied machine learning products at scale (applied research, design, implementation, production, and evaluation).
ML Frameworks: 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow.
Production ML: 4+ years of professional experience in building services to host machine learning models in production at scale.
LLMs/GenAI: 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases.
Cloud Platforms: 4+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).