Principal, Software Engineer (distributed Systems)

Workday Workday · Enterprise · Pleasanton, CA

Principal Software Engineer role focused on designing and leading the architecture of core product microservices and large-scale distributed systems for Workday's Developer Platform. The role emphasizes building resilient, scalable backend infrastructure, driving cross-organizational technical strategy, and improving observability and operational excellence. While the role leverages AI-assisted development tools and integrates AI capabilities, its primary focus is on the underlying distributed systems and platform infrastructure, not on shipping AI models or agents as the core product.

What you'd actually do

  1. Lead the architecture, design, and evolution of core product microservices, ensuring they are secure, scalable, decoupled, and highly available.
  2. Design and deliver large-scale, resilient distributed systems that support mission-critical product features with strong performance and reliability guarantees.
  3. Drive cross-organizational technical strategy to improve the agility, modularity, and operational excellence of our microservices ecosystem.
  4. Identify, define, and drive solutions for complex, ambiguous product and domain challenges that span multiple services and business units
  5. Establish and champion best practices for domain-driven design, distributed systems, strict API contract management, and observability.

Skills

Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
  • 12+ years of software engineering experience
  • designing, building, and maintaining large-scale distributed systems
  • production-grade microservice architectures
  • hands-on experience with object-oriented or functional programming languages, specifically Java or Scala.
  • delivering and scaling large distributed production services to a global enterprise customer base.
  • 5+ years of experience building, operating, and driving cost-optimization for products within large-scale cloud environments, with deep expertise in AWS and/or GCP (including S3, Lambda, EC2).
  • 5+ years of hands-on experience with containerization and orchestration technologies, specifically Docker and Kubernetes.
  • Integrate AI capabilities directly into scalable software solutions while adhering to Responsible AI practices.
  • Demonstrated proficiency with AI-assisted development tools (Cursor, Claude Code, GitHub Copilot, or similar), including the ability to direct, review, and validate AI-generated code.
  • Expert-level programming proficiency in Java, Scala

Nice to have

  • AI-assisted engineering tools
  • modern coding techniques

What the JD emphasized

  • deep expertise in distributed systems and microservices architecture
  • complex technical challenges
  • large-scale distributed systems
  • production-grade microservice architectures
  • large distributed production services
  • large-scale cloud environments
  • containerization and orchestration technologies
  • integrate AI capabilities directly into scalable software solutions
  • Responsible AI practices
  • AI-assisted development tools