Senior Software Engineer - AI Tools

Workday•Pleasanton, CA

15h•Hybrid

About The Position

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.

Requirements

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

Nice To Haves

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

Responsibilities

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