About the Team
Welcome to the AI Tools team at Workday! We identify, deploy, and scale AI-powered tools that eliminate friction from the developer experience - and extend those capabilities to the broader organization as they mature. We build the AI platform layer that powers code generation, AI-assisted code review, agentic workflows, and enterprise-wide developer tooling. We own the MCP registry and gateway that connects Workday's developers to AI capabilities, and we build the technical guardrails that operationalize how AI is used responsibly across the company. If you want to do high-impact AI infrastructure work in enterprise software, we'd love to hear from you.

About the Role

The Workday AI Tools team is looking for a senior engineer who thrives at the intersection of AI, platform engineering, and developer experience. You'll design and build systems that thousands of Workday engineers rely on every day - from LLM gateways and MCP server infrastructure to AI-native agents and compliance tooling. You'll help define how we integrate emerging AI capabilities into our platform, and you'll be a technical anchor on a team that moves fast and takes quality seriously.

You'll also work directly with the engineers using these tools - through office hours, Slack support, and our Champions program - and your work will be shaped by their feedback.

In this role you will:

- Design and build the AI platform layer: LLM gateways, MCP registries, abstraction APIs, and shared infrastructure that teams across Workday build on

- Architect and implement AI agents and automation that improve the developer workflow - code review, documentation, testing, and beyond

- Drive the evaluation and integration of AI model providers, keeping a strong eye on cost, safety, and performance tradeoffs

- Serve as a scout for emerging AI capabilities - track new models, tools, and frameworks, and make recommendations to engineering leadership on when to adopt, evaluate, or pass

- Lead technical design on complex, cross-cutting projects in partnership with Security, DevEx, and infrastructure teams

- Build observability and governance tooling that gives the organization visibility into how AI tools are being used

- Operationalize AI policy and compliance requirements into our platform

About You

Basic Qualifications

-5+ years of software engineering experience

- 3+ years building and operating backend services or platform infrastructure in production

- Strong proficiency in Python and/or TypeScript

- Hands-on experience building or integrating with LLM APIs (OpenAI, Anthropic, etc.) and familiarity with prompt engineering, evaluation pipelines, and model selection tradeoffs

- Robust understanding of AI security principles and responsible AI practices - including prompt injection, model misuse, data leakage risks, output validation, and operationalizing policy guardrails in production AI systems

- Genuine excitement about being on the leading edge of AI - you follow new model releases, tooling shifts, and emerging frameworks closely, and you bring that energy into what the team builds

Other Qualifications

- Hands-on experience designing and building AI agents, including fluency with agentic frameworks and patterns such as ReAct - and practical experience shipping agents that are reliable in production

- Experience building MCP servers, Claude skills, or similar tool-use integrations that extend AI capabilities to real workflows

- Comfort designing REST APIs and service-oriented architectures

- Experience with container orchestration (Kubernetes, Docker) and deploying services to cloud environments; experience with workflow orchestration tools and infrastructure-as-code is a plus

- Understanding of enterprise security patterns: authentication, authorization, SSO, and secrets management

- Exposure to observability tooling - logging, metrics, tracing - and a habit of building systems that are easy to monitor

- Comfort partnering directly with the engineers who use your tools - you see user feedback, support channels, and adoption work as part of the job, not a distraction from it

- Strong written and verbal communication skills; able to drive alignment across engineering, security, and product stakeholders

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.CA.Pleasanton

Primary Location Base Pay Range: $176,000 USD - $264,000 USD

Additional US Location(s) Base Pay Range: $148,200 USD - $264,000 USD

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.