About the company
Vapi is the platform for deploying voice agents that know your business and can listen, adapt, and resolve in minutes. Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life, Uber, NHS. Trusted by 1 million developers building the future of voice agents. Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised.
Responsibilities
- Map and instrument Vapi’s path from task to production, identify the largest constraints on agent effectiveness, and ship your first improvements to our sandbox environment, developer tooling, or validation infrastructure.
- Launch the first production workflow in Vapi’s internal software factory. Give background agents the context, tools, sandbox, telemetry, and automated quality gates required to turn scoped tasks into review-ready PRs backed by real evidence.
- Own and launch Vapi’s platform for autonomous, background engineering. Build a harness that lets agents place real calls, measure latency, conversation quality, inspect telemetry, and iterate to a verified result.
Requirements
- You have built internal platforms, developer tooling, or infrastructure that materially changed how engineers build, test, and ship software.
- You are a hands-on engineer with strong software fundamentals across distributed systems, platform architecture, API design, CI/CD, and monorepo or large-codebase workflows.
- You have practical experience building agent harnesses and using coding agents such as Claude Code, Codex, Cursor, or open-source equivalents on real engineering work.
- You know how to design secure agent interfaces, MCP integrations, and sandboxed runtimes where agents can call APIs, run CLI commands, and use general-purpose tools safely.
- You have built or operated online and offline LLM evaluation systems and can reason clearly about accuracy, latency, reliability, and cost.
- You are fluent in at least one of TypeScript, Python, or Go and comfortable working across containers, databases, queues, orchestration systems, and modern cloud infrastructure.
- You stay current on frontier models and techniques such as prompt caching, context compression, retrieval, and multi-agent coordination.
Conditions
- Real stake: competitive salary and equity ownership
- Comprehensive health coverage: medical, dental, and vision plans
- Team love: quarterly off-sites
- Flexible time off
- Catered meals, transportation, equipment, and a $10k annual L&D budget