Voice AI that resolves, not transfers.
Most phone systems trap callers in menus and scripts. Vapi is the platform for deploying voice agents that know your business and can listen, adapt, and resolve in minutes.
The numbers: 1 billion calls. 1 million developers. 10x enterprise ARR growth
The customers: Amazon Ring, ServiceTitan, New York Life, Intuit, Kavak, and thousands more, from YC startups to the Fortune 500
The news: a $50M Series B led by Peak XV Partners, with Bessemer Venture Partners, Kleiner Perkins, M12 (Microsoft's Venture Fund), Y Combinator, and our earlier backers. Total raised: $72M
Vapi builds voice AI that resolves, not transfers. Our platform powers over 1 billion calls for more than 1 million developers, and our enterprise business has grown 10x over the past year — with customers ranging from fast-moving startups to Fortune 500 companies. We recently closed a $50M Series B to keep pushing what's possible when an AI agent can actually get the job done on a phone call.
The RoleAs Vapi product scales, we have specialized the product engineering team to focus on outcomes across the customer lifecycle. One key area here is agent building and model management. Our customers expect a lot of their Vapi agents, and our Agent Platform team ensures they have the latest models available and all the configuration to make those agents successful at scale. You'll drive impact through the quality of your product thinking and your ability to move fast with engineering.
What You'll DoOwn how customers create, configure, and manage voice agents on Vapi. These are the core building blocks of the platform.
Drive the integrations and tools that agents can call on, expanding what they're capable of doing on a call.
Run the full lifecycle of every model Vapi supports, from evaluation and onboarding through deprecation.
Build the process that keeps Vapi at the frontier, so the latest models get added quickly and reliably, every time.
Define how model performance gets measured, so every model on the platform is judged on evidence, not intuition.
Run experimentation and research into the latest agentic harness opportunities, translating new techniques into features that help customers get more out of the models they use.
Take on the sprawl of agent configuration, currently thousands of possible parameters that can be set, and figure out how to make that power feel simple.
5+ years of experience as a PM, most of it spent building and operating technical products at meaningful scale inside medium to large sized tech companies.
A strong technical foundation — you don't need to have shipped production code, but you can reason through system design and architecture trade-offs with engineers as a peer.
Exceptional communication and presentation skills, and the range to use them: aligning engineers, briefing executives, and presenting to external clients and partners with equal credibility.
A track record of owning outcomes, not process — you talk about the problem you solved and the impact it had, not the framework you followed to get there.
Genuine customer centricity. You've built B2B or enterprise products, and you default to talking about customers, not features.
You've managed AI model integrations across TTS, STT, or LLM providers.
You have direct experience in voice AI.
You've built developer platforms, infrastructure products, or API-first products.
You've developed model evaluation or benchmarking systems.
Base salary ranging from $240,000 - 270,000, plus equity. Vapi also offers comprehensive health coverage, flexible time off, and the standard perks of a fast-growing SF startup (catered meals, commuter support, and a learning & development budget).
Skills Required
- 5+ years of experience as a Product Manager building and operating technical products at scale in medium to large tech companies.
- Strong technical foundation; able to reason about system design and architecture trade-offs with engineers.
- Exceptional communication and presentation skills for aligning engineers, briefing executives, and presenting to clients.
- Proven track record of owning outcomes and driving measurable impact.
- Customer-centric experience building B2B or enterprise products.
- Experience managing AI model integrations across TTS, STT, or LLM providers.
- Direct experience in voice AI.
- Experience building developer platforms, infrastructure products, or API-first products.
- Experience developing model evaluation or benchmarking systems.
Vapi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Vapi and has not been reviewed or approved by Vapi.
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Equity Value & Accessibility — Equity is presented as meaningful ownership in a fast‑growing startup, with substantial grants emphasized and an explicit “ownership culture.” This positioning gives employees a real financial stake in the company’s growth.
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Healthcare Strength — Health coverage is described as comprehensive medical, dental, and vision, with additions like One Medical and Spring Health and claims of 100% employer‑paid coverage for employees in some materials. This breadth indicates strong protection for employees and families.
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Wellbeing & Lifestyle Benefits — Everyday perks include a $10,000 annual learning budget, daily catered meals, commuter support, fitness memberships (e.g., Equinox), and quarterly offsites. Public materials also cite significant per‑employee investment beyond salary.
Vapi Insights
What We Do
Vapi lets enterprises deploy human-like voice agents in minutes. Whether you’re building a voice product or trying to handle millions of calls, Vapi’s reliable infrastructure and flexible APIs make it easy. Everyone from YC startups to Fortune 500 companies rely on Vapi because it is: Flexible: Plug in your APIs, your customer data, your models Scalable: Handle millions of calls with <500ms latency Secure: LLM guardrails, HIPAA, SOC-2 Helping enterprises over this challenge, Vapi, has raised $20 million in Series A funding, led by Bessemer Venture Partners with participation from Abstract Ventures, AI Grant, Y Combinator, Saga Ventures, and Michael Ovitz.
