Vapi
Member of Technical Staff, Agentic Developer Experience
San Francisco · Staff+
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About the role
- - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life
- - Trusted by 1 million developers building the future of voice agents
Responsibilities
- 90 Days: 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.
- Create the foundation that accelerates every engineer and puts Vapi on a credible path to shipping 10× faster.
Requirements
- 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, and you know when the newest tool is useful versus distracting.
- 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.
Compensation
- More: catered meals, transportation, equipment, and a $10k annual L&D budget
Benefits
- Real stake: We offer a competitive salary and equity ownership
- Comprehensive health coverage: medical, dental, and vision plans
- Flexible time off: take what you need
Company info
- The fastest path to customer value usually wins. - Seek raw input: We go directly to customers, data, and teammates instead of relying on summaries or assumptions. - It's our problem: We operate as one team.
- Build something worthy of love: Craft matters. We build products and experiences customers genuinely love, not just tolerate.
- What We Offer:
This listing is sourced directly from Vapi's careers page and normalized into a canonical job model.