Principal Software Engineer (gtmo/mesh)

ZoomInfo ZoomInfo · Enterprise · CA · Remote · 965 Product Management - AI & Strategy

Principal Software Engineer to own and build features across the full stack of ZoomInfo's internal AI platform (Mesh), focusing on AI agents, orchestration workflows, microapp infrastructure, and LLM integrations. The role involves full-stack development, cloud infrastructure, incident response, and mentoring engineers, with a preference for experience with LLMs, RAG, and workflow orchestration systems.

What you'd actually do

  1. Building and improving core platform capabilities: AI agents, orchestration workflows, microapp infrastructure, LLM integrations
  2. Owning features across the full stack — React frontends, backend APIs, cloud infrastructure — from design through production
  3. Developing SDKs and tooling for engineers who build on top of Mesh
  4. Responding to production incidents and shipping fixes
  5. Championing quality and reliability — tests, coverage, habits that prevent regressions

Skills

Required

  • 12+ years of software engineering experience
  • track record of delivering reliable, scalable systems
  • Strong full-stack skills
  • React/TypeScript
  • backend services
  • cloud infrastructure
  • cloud-native environment
  • Kubernetes
  • Cloud Functions
  • Pub/Sub
  • managed databases
  • SQL
  • NoSQL databases
  • Postgres
  • MongoDB
  • Redis
  • owning production systems
  • logs
  • incident triage
  • fixes under pressure
  • software quality
  • testing strategy
  • code review
  • regression prevention
  • Security awareness
  • Clear communication
  • fast-moving, high-ownership environments

Nice to have

  • Experience with LLMs — Claude, GPT, Llama
  • building applications on top of them
  • context engineering
  • RAG patterns
  • MCP or AI tool integrations
  • Temporal or similar workflow orchestration systems
  • vector databases — Pinecone, pgvector, etc.
  • building developer-facing SDKs or platform tooling
  • CI/CD pipelines, particularly GitHub Actions

What the JD emphasized

  • AI agents
  • orchestration workflows
  • LLM integrations
  • developer-facing SDKs
  • platform tooling
  • cloud infrastructure
  • production incidents
  • incident triage
  • fixes under pressure
  • regression prevention

Other signals

  • AI agents
  • orchestration workflows
  • LLM integrations
  • developer-facing SDKs
  • platform tooling