Are you driven to apply innovative AI to real-world enterprise challenges? As an AI/ ML Engineer on the Workday Adaptive Planning team, you’ll help redefine how financial planning is done at scale—by designing and building intelligent, agentic workflows that power the next generation of FP&A solutions. You’ll be at the forefront of bringing "AI-first" thinking into production, developing enterprise level intelligent systems that automate, adapt, and assist users throughout the financial planning journey. Your work will directly impact thousands of global enterprises and millions of end users. What You’ll Do:Technically leadership: lead design and development of sophisticated AI agents that reason, learn, and interact across complex business processes to enhance productivity and decision-making. Integrate AI Frameworks: Embed secure, scalable, and reliable agentic capabilities into core Adaptive Planning features. Partner Cross-Functionally: Collaborate with extraordinary engineers and product managers to bring ideas to life.?Own Projects End-to-End: Lead the full AI development lifecycle—problem framing, data prep, design & development, deployment, evaluation, and continuous improvement. Leverage Rich Planning Data: Harness Workday Adaptive Planning’s vast enterprise datasets to tune and optimize your AI models for high-value outcomes. Mentorship: Provide technical guidance to junior engineers. Conduct critical code reviews and unblock the team on deep technical hurdles. We’re looking for bold thinkers with strong technical and a product mindset. You’ll need to move fast, think big, and stay grounded in solving real customer problems through AI. If this sounds like your kind of challenge, we’d love to talk. About You. Basic Qualifications 4 years experience working on a data science, machine learning or related software development team . years experience with Python supporting ML/ AI libraries, with experience in shipping secure, production solutions . years of experience in object oriented programming with Java. 5 years experience in Saas software development. Other Qualifications. Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering. A PhD or MS degree in a relevant field, such as Computer Science, Mathematics, or Engineering is highly desired. Extensive experience with large language models (LLM), retrieval augmented generation (RAG) systems, semantic search and text embedding models, transformer neural networks, and related frameworks. Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker) and data engineering pipelines (e.g. ETL)Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring. An ability to balance speed with delivering high-quality, practical solutions. Shown perseverance in overcoming significant problems. You have a strong focus on delivering high-quality software products, continuous innovation, and you value test automation and performance engineering. Workday Pay Transparency Statement. 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. Primary Location: USA. CO. Boulder Primary Location Base Pay Range: $171,600 USD - $257,400 USD Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD - Additional Considerations: The application deadline for this role is the same as the posting end date stated as below: 05/20/2026 Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.