Software Development Engineer - AI Tools

Workday Workday · Enterprise · Atlanta, GA

Software Development Engineer focused on building the AI platform infrastructure for enterprise AI tools at Workday. This includes MCP servers, LLM gateway, developer tooling, code generation, AI-assisted code review, and agentic workflows, with a strong emphasis on responsible AI and operationalization.

What you'd actually do

  1. Build and maintain MCP servers, AI integrations, and developer tools that improve the daily workflow for Workday's engineering org
  2. Write scripts and automation that streamline AI tool onboarding, configuration, and fleet management
  3. Instrument services with logging and monitoring to keep our platform observable and reliable
  4. Work with Security and compliance partners to implement policy requirements in our tooling
  5. Participate in code review and help maintain a high standard for the team's codebase

Skills

Required

  • 3+ years of software engineering experience
  • Production experience building backend services or developer tooling in Python and/or TypeScript
  • Familiarity with LLM APIs and basic prompt engineering concepts
  • Working understanding of AI security and responsible AI principles
  • Genuine excitement about the cutting edge of AI

Nice to have

  • Understanding of AI agent architectures, including the ReAct pattern and how agents reason, plan, and use tools iteratively
  • Experience building MCP servers, skills, or tool-use integrations
  • Experience building or consuming REST APIs
  • Working knowledge of Docker and container-based deployments
  • Experience with Kubernetes
  • Exposure to workflow orchestration or infrastructure-as-code tooling
  • Familiarity with DevOps practices and CI/CD systems
  • Understanding of authentication and authorization fundamentals (OAuth, SSO, API keys)
  • Comfort working in a cloud environment (AWS, GCP, or Azure)
  • Experience adding observability to services - logging, metrics, alerting
  • Comfort partnering directly with the engineers who use your tools
  • Strong written communication skills

What the JD emphasized

  • production code
  • high-impact
  • high-ownership
  • small team that moves quickly
  • work directly with the engineers using these tools
  • Production experience building backend services or developer tooling
  • Working understanding of AI security and responsible AI principles
  • Genuine excitement about the cutting edge of AI
  • hands-on experience building or experimenting with agents is a plus
  • Experience building MCP servers, skills, or tool-use integrations
  • Comfort working in a cloud environment
  • Comfort partnering directly with the engineers who use your tools

Other signals

  • AI platform layer
  • code generation
  • AI-assisted code review
  • agentic workflows
  • enterprise-wide developer tooling
  • MCP registry and gateway
  • technical guardrails
  • operationalize how AI is used responsibly