ABOUT US

Mira Mace pairs Medicare beneficiaries with a dedicated healthcare advocate who navigates appointments, insurance, and care coordination on their behalf. Our customers get the support of caring nurses while AI agents handle the tedious backend work — all covered by Medicare.

Today, 24/7 personalized health assistance is only available to the rich or extremely sick. Our vision is for everyone to be able to afford a health assistant who knows your health history deeply, navigates the healthcare system on your behalf, and propels you to become the healthiest version of yourself.

Our founding team brings a mix of strong technical experience from companies like Google, Meta, Dropbox, and Amazon, along with serial startup experience ranging from early bootstrapped ventures to Series D scale-ups. We are backed by Foundation Capital, DefineVC and top Silicon Valley angel investors.

WHAT WE'RE LOOKING FOR

We're looking for an engineer to own our voice AI end to end: the calling pipeline, the quality of every conversation that runs through it, and what we build next. Engineers take a company goal, find where the leverage is, turn it into a roadmap, ship, and measure whether it moved the number.

Our problem space runs on the phone. Getting a customer set up takes a real conversation, and much of the work we do on their behalf can only happen by calling institutions — which means automated phone menus, long holds, transfers, and getting a specific outcome out of someone who didn't expect the call. Many of our customers are older and expect to be spoken with, not processed. Voice AI has to clear that bar, and clearing it is the product.

You'll own the full real-time stack and the systems that make it measurably better with every release: evaluation for calls, replayable regression suites, and the tooling that tells us why a call went wrong before a customer does. You'll work directly with the founders and with the team that listens to these calls every day.

This role is specifically for someone with real voice experience. If you've shipped a production real-time voice agent, we want to talk.

RESPONSIBILITIES

Turn goals into a roadmap. Take a goal like "more of the people who sign up get through their first call" or "more insurer calls end with the answer we needed," break it into the problems behind it, size them, and decide what to build first. You write the plan, defend the tradeoffs, and change it when the data says to.

Own the voice pipeline. Build and operate the real-time stack — telephony, streaming speech-to-text, LLM orchestration, text-to-speech, endpointing, barge-in, and the latency budget that keeps a conversation feeling human.

Drive call quality relentlessly. Define what a good call is, measure it, and move the number. Build the evaluation harness — replayable audio and transcripts, regression suites, per-turn scoring — so quality changes are provable rather than anecdotal.

Handle the real world. Automated phone menus and DTMF, holds and transfers, voicemail, dropped calls and retries, noisy lines, accents, interruptions, and speaking clearly with an older audience.

Scale calling volume reliably. Make the system hold up across thousands of calls a day, with clean handoffs to a human when the agent should stop.

Close the loop with the people who hear every call. Turn what our team observes on real conversations into prompt, model, and pipeline changes, fast.

Ship fast and iterate with real users. Deploy to production, listen to real conversations, and improve from them — in days, not quarters. Success is the business metric the work was meant to move, not the ship date.

Lay the foundation for scale. Make architectural decisions in the voice stack that hold up from hundreds of calls a day to hundreds of thousands.

QUALIFICATIONS

You've built and shipped real-time voice AI to production — not a demo, but a system that took real calls with real people.

Hands-on depth across the voice stack: streaming speech-to-text, text-to-speech, turn detection and endpointing, barge-in, and latency optimization under a real-time budget.