Member of Technical Staff, Forward Deployed

Vapi (/ˈVɑːpi/): Voice AI that resolves, not transfers 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 Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised Try talking to Vapi now! Why We're Hiring This Role Our Enterprise ARR has grown 10x — customers like Amazon Ring, NY Life and Intuit deploy in weeks and expand rapidly when we support them well. Customer deployments now consume most of our current FDE capacity, which means platform roadmap work competes directly with delivery. We're opening more seats this quarter in San Francisco and New York to take on that unowned roadmap work. Steady-state accounts are handing off to our Agent Engineering team so FDEs can return to building the platform, not just running it. Unlike a solutions engineer, an FDE ships code: into customer repos, into Vapi's GitOps configs, and into the Vapi platform itself. This isn't CRUD engineering. You're building real-time, latency-sensitive systems that orchestrate multiple providers — speech-to-text, LLMs, text-to-speech, telephony — simultaneously, in production, at enterprise scale. It's the kind of systems problem most engineers only get to touch on infra teams at much larger companies, and you'll own it end to end. What You'll Do 30 [... source excerpt omitted ...] ternal tooling or product contributions that make the next similar deployment materially faster 90 Day: Establish a process or infrastructure the team didn't know it needed What You'll Own Lead deployment engagements end to end for assigned enterprise customers, from scoping through go-live and handoff Build production-ready Vapi deployments (assistants, squads, tools, structured outputs, telephony/SIP, webhooks, integrations) Debug live production issues across call records, app logs, provider request/response, and infra metrics Own customer-facing GitOps repos and dedicated cluster configuration Manage technical and executive stakeholders across technical and non-techn [... source excerpt omitted ...] ple hats in a scrappy, resource-constrained environment Can communicate clearly with both technical and non-technical stakeholders Conceptual understanding of working with AI in production Hard Skills Backend: Node.js, Express, FastAPI, Django, or Flask Frontend: React, Next.js, Vue, or Tailwind Language: TypeScript or Python Database: SQL, MongoDB, DynamoDB, or Redis Deployment: AWS, GCP, Azure, Vercel, or Railway Coding Tools: Cursor, Claude Code, Codex, or Windsurf Nice to Have AI/ML: LLM APIs, RAG, vector databases (Pinecone, pgvector), self-hosted models Infra: Docker, Kubernetes, IaC Real-time: WebSockets, SSE, WebRTC, SIP Led a project without a management titl