It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. Backed by Greylock and Sequoia.
About the role
Build voice AI agents. Design and ship agentic voice applications — intent interpretation, multi-step reasoning, tool invocation, and action on the caller's behalf — together with the CTI, CCaaS, and telephony integrations that make them usable in production. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Forward deployed or customer-embedded delivery. Prior work as a forward deployed engineer, solution engineer, or in professional services, delivering software inside a customer's environment
- Voice and contact center technology. Telephony and contact center platforms, IVR, speech recognition and synthesis, streaming audio, and real-time latency optimization
- Conversation design partnership. Experience working alongside conversation or content designers, contributing to dialogue flow, tone, and error-recovery design
- Evaluation and observability tooling. Evaluation frameworks, prompt and instruction management tooling, tracing for LLM applications, and analysis of production call transcripts at scale
- Enterprise domain depth. Customer service, contact center operations, sales, or enterprise workflow, at a depth sufficient to challenge a requirement rather than only implement it
- Years of Experience. At least 10 years of experience in software engineering with at least 2 years of experience in deploying contemporary AI solutions at customers
More about this role
The Forward Deployed Engineer, Voice AI Agent Engineering designs, builds, ships, and operates voice AI agents whose core behavior is model-driven rather than explicitly authored — conversational and agentic experiences that interpret caller intent over a live audio channel, reason over context, invoke tools, and act on the caller's behalf. The engineer works across the full lifecycle: shaping ambiguous call flows and telephony requirements into precise specifications, authoring the instructions and prompts that govern voice agent behavior, proving through automated evaluation that the result behaves correctly on real calls. This is not a machine learning or AI research role — the engineer does not train foundation or speech models — but it is distinct from traditional software engineering, where systems follow deterministic call-flow logic rather than selecting execution paths at runtime.
Two things follow, and voice makes both harder. First, the agent's most important logic often lives in natural language — instructions, prompts, tool descriptions, and guardrails — which must be engineered, versioned, and reviewed with the same discipline as code, while also holding up under...
Browse similar: AI jobs · AI startup jobs · Startup jobs