Skills

Full description

Health system call centers can’t keep up with patient demand. 85% of patients who can’t get through never call back. They go elsewhere, and appointments that should have been booked never are
We’re building AI Voice Agents that pick up every call and handle the full conversation: scheduling, rescheduling, cancellations, confirmations, FAQs, and intake. They work by integrating directly with the EHR and telephony stack in real time
We’re hiring a Software Engineer to build the systems these agents run on: the voice pipelines, EHR integrations, and services that take a call from “hello” to a booked appointment. It’s a mid-level role on a small team that ships every day, with a lot of room to grow into harder problems
Design and build backend services in Python that power real-time voice agents: call orchestration, conversation state, tool execution, and EHR write-back
Architect low-latency pipelines connecting telephony, ASR, LLMs, and TTS into a single conversational loop
Lead integrations with healthcare systems (like Epic, Cerner, athena, and others) for scheduling, eligibility, and intake
Drive design decisions on APIs, data models, and event-driven workflows, and mentor other engineers on the team
Partner with AI, product, and operations to ship features patient access teams actually use
Set the bar for what ships: latency, reliability, observability, and release readiness

4+ years of backend software experience, primarily in Python
A track record of designing and shipping production services, APIs, and data models that others build on
Deep experience with async, event-driven, or real-time systems
Strong fundamentals in testing, LLM evaluation, observability, and reliability
Bias for action, an ownership mindset, and the judgment to know when to move fast and when to slow down
An intuition for how people interact with automated assistants through voice and text, where the rules are different than icons and buttons
A patient-centered mindset. You design for the person on the other end of the line, not just the metrics

Senior Software Engineer (Voice Agents)

Compensation

$170K–$230K / yr

Location

Mountain View, CA, United States

Work setup

Onsite

Seniority

Senior

Employment

Not specified

Experience

4+ years

Health system call centers can’t keep up with patient demand. 85% of patients who can’t get through never call back. They go elsewhere, and appointments that should have been booked never are
We’re building AI Voice Agents that pick up every call and handle the full conversation: scheduling, rescheduling, cancellations, confirmations, FAQs, and intake. They work by integrating directly with the EHR and telephony stack in real time
We’re hiring a Software Engineer to build the systems these agents run on: the voice pipelines, EHR integrations, and services that take a call from “hello” to a booked appointment. It’s a mid-level role on a small team that ships every day, with a lot of room to grow into harder problems
Design and build backend services in Python that power real-time voice agents: call orchestration, conversation state, tool execution, and EHR write-back
Architect low-latency pipelines connecting telephony, ASR, LLMs, and TTS into a single conversational loop
Lead integrations with healthcare systems (like Epic, Cerner, athena, and others) for scheduling, eligibility, and intake
Drive design decisions on APIs, data models, and event-driven workflows, and mentor other engineers on the team
Partner with AI, product, and operations to ship features patient access teams actually use
Set the bar for what ships: latency, reliability, observability, and release readiness

4+ years of backend software experience, primarily in Python
A track record of designing and shipping production services, APIs, and data models that others build on
Deep experience with async, event-driven, or real-time systems
Strong fundamentals in testing, LLM evaluation, observability, and reliability
Bias for action, an ownership mindset, and the judgment to know when to move fast and when to slow down
An intuition for how people interact with automated assistants through voice and text, where the rules are different than icons and buttons
A patient-centered mindset. You design for the person on the other end of the line, not just the metrics