Senior Software Engineer (Gen AI)

About the role

We are seeking AI/ML Engineers to help redefine how financial planning is done at scale. You will lead the design and development of sophisticated AI agents that reason, learn, and interact across complex business processes to enhance productivity and decision-making. You will integrate AI frameworks, partner cross-functionally, and own projects end-to-end. Your work will directly impact thousands of global enterprises and millions of end users.

Responsibilities

• Lead design and development of sophisticated AI agents that reason, learn, and interact across complex business processes to enhance productivity and decision-making.
• Embed secure, scalable, and reliable agentic capabilities into core Adaptive Planning features.
• Collaborate with extraordinary engineers and product managers to bring ideas to life.
• Own the AI development lifecycle from problem framing to deployment, evaluation, and continuous improvement.
• Leverage rich planning data to tune and optimize AI models for high-value outcomes.
• Mentor junior engineers and provide technical guidance.
• Conduct critical code reviews and unblock the team on deep technical hurdles.

Requirements

• 4+ years experience working on a data science, machine learning or related software development team.
• 4+ years experience with Python supporting ML/AI libraries, with experience in shipping secure, production solutions.
• 4+ years of experience in object-oriented programming with Java.
• 5+ years experience in SaaS software development.
• 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, MCP, langgraph, vibe coding, 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.
• Show perseverance in overcoming significant problems.
• Have a strong focus on delivering high-quality software products, continuous innovation, and value test automation and performance engineering.

Qualifications

• Basic qualifications: 4+ years experience working on a data science, machine learning or related software development team; 4+ years experience with Python supporting ML/AI libraries, with experience in shipping secure, production solutions; 4+ years of experience in object-oriented programming with Java; 5+ years experience in SaaS software development; Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering.
• Other qualifications: 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, MCP, langgraph, vibe coding, 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; Show perseverance in overcoming significant problems; Have a strong focus on delivering high-quality software products, continuous innovation, and value test automation and performance engineering.

Skills

• Strong technical and product mindset.
• Driven to apply innovative AI to real-world enterprise challenges.
• Experience with large language models (LLM), retrieval augmented generation (RAG) systems, semantic search and text embedding models, MCP, langgraph, vibe coding, 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.

Benefits

Workday offers a competitive compensation package, including the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. We also provide a flexible work schedule, with at least half of your time each quarter spent in the office or in the field with our customers, prospects, and partners. We are committed to providing an accessible and inclusive hiring experience and maintaining a strong community. We are an Equal Opportunity Employer and committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills.

Pay

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.

Schedule

Our approach to flexible work combines the best of both worlds: in-person time and remote. We enable 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).

Location

Primary Location: USA.CO.Boulder

Additional US Location(s): Primary Location Base Pay Range: $171,600 USD - $257,400 USD Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD