Distributed Systems Software Engineer - Public Cloud (mid/senior/lead/principal)

Salesforce Salesforce · Enterprise · San Francisco, CA +2

Salesforce is seeking a Distributed Systems Software Engineer to build and maintain a large-scale distributed systems engineering platform. The role involves delivering cloud infrastructure automation, designing resilient distributed systems, and developing microservices. A key aspect is integrating AI agents into human workflows, contributing to shared system context for AI reliability, and critically evaluating AI-generated code. The role requires advanced prompt engineering skills and using AI tools to enhance the development workflow.

What you'd actually do

  1. Deliver cloud infrastructure automation tools, frameworks, workflows, and validation platforms on our public cloud platforms such as AWS, GCP, Azure, or Alibaba
  2. Designing, developing, debugging, and operating resilient distributed systems that run across thousands of compute nodes in multiple data centers
  3. Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools (Cursor, Windsurf, Claude, OpenAI API) to deliver secure, optimized, and high-quality code.
  4. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
  5. Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance.

Skills

Required

  • A related technical degree required
  • 3+ years backend software development experience
  • Deep knowledge of programming in Java, GoLang, Python, or Ruby
  • Experience owning and operating multiple instances of a critical service
  • A demonstrated, genuine AI-first approach to engineering.
  • Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows
  • Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
  • Experience with Agile development methodology and Test Driven Development
  • Experience with critical infrastructure services including, monitoring, alerting, logging, and reporting applications

Nice to have

  • Experience with distributed database system and relational databases like postgres is a plus.

What the JD emphasized

  • Advanced prompt engineering skills
  • AI agents integrate seamlessly into human workflows
  • Critically evaluate code (Human or AI-generated)

Other signals

  • AI agents integrate seamlessly into human workflows
  • AI outputs reliable, secure, and production-ready
  • AI as a core part of your development workflow