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.
We've felt the pain ourselves — the endless back-and-forth with insurance, surprise bills, and the lack of clarity when you just need answers. Too many people fall through the cracks, and we're determined to change that.
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 Microsoft, Google, Meta, 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 AI engineer to own the loop that turns real-world patient interactions into better AI agents — from eval infrastructure to production-grade systems. You'll own the systems that make our agents smarter with every patient interaction — from the voice AI that activates patients and handles calls to insurances, vendors, and providers, to the autonomous workflows that orchestrate end-to-end care delivery.
You'll work directly with the founders to build production systems that learn and improve from real-world usage. You'll design the eval pipelines, capture the right signals from product usage, and create the reinforcement learning loops that drive continuous quality improvement across every agent we ship.
If you've built AI systems that get better with usage and want to apply that experience to healthcare — where every improvement directly impacts patient outcomes — we'd love to talk.
Responsibilities
Launch and scale high-quality AI agents. Build and deploy voice AI for automating patient activation and outbound calls to insurances, vendors, and providers. Design individual agents that orchestrate end-to-end workflows such as DME delivery, prior authorizations, and care coordination. Build copilots that assist and nudge advocates in real time.
Build the eval and reinforcement learning pipeline. Set up the evaluation infrastructure that measures agent quality across every interaction. Capture the right data from product usage, build the feedback loop, and implement RL pipelines so that agent performance improves continuously with real-world usage. Create the usage-driven product improvement flywheel.
Scale AI Nurse by composing multiple agents. Bring together voice, workflow, and copilot agents into a unified AI Nurse experience. Ensure that as we scale, each agent reinforces the others through shared learning and a consistent improvement loop.
Ship fast and iterate with real users. Deploy to production, monitor how agents perform with actual patients, and improve based on real conversations. Own the tight loop from usage data to system-level improvements.
Shape the technical roadmap. Work with the founders to decide what to build next. Bring deep knowledge of what's possible with current AI capabilities and help us make smart bets on where the technology is heading.
Lay the foundation for scale. Make architectural decisions that will hold up as we grow from hundreds of patients to hundreds of thousands. Document systems, establish best practices, and build with the next engineer in mind.
Qualifications
You've built AI agents or LLM-powered systems from scratch and shipped them to production — not just demos, but systems handling real interactions with real users at scale.
You have hands-on experience building evaluation pipelines for AI systems — designing metrics, capturing signals from production usage, and using that data to systematically improve agent quality.
You have experience with reinforcement learning from human feedback (RLHF), reward modeling, or other feedback-driven improvement loops for LLM-based systems.
You've monitored and debugged AI systems in production — you know what it takes to keep agents reliable when they're interacting with real people.
You're comfortable with ambiguity. The playbook doesn't exist yet, and you're excited to build it.
Nice to Have
Experience in healthcare, health tech, or regulated industries (HIPAA, PHI handling).
Familiarity with Medicare, insurance workflows, or clinical operations.
Experience with voice AI systems — speech-to-text, text-to-speech, and real-time voice orchestration.
Background in RAG systems, vector databases, and knowledge retrieval pipelines.
Contributions to open-source AI projects or a portfolio of side projects that show your range.
Who You Are
Beyond technical skills, we're looking for someone who embodies the attributes that make great engineers at an early-stage company:
Proactive. You move quickly and take a forceful stand without being abrasive. You act without being told what to do and bring new ideas to the company.
Analytically sharp. You structure and process qualitative or quantitative data and draw penetrating insights. You learn quickly and absorb new information with ease.
High standards with attention to detail. You expect nothing short of the best from yourself and your team. You don't let important details slip through the cracks or derail a project.
Passionate and open. You exhibit enthusiasm and a can-do attitude over your work. You solicit feedback often and react calmly to criticism or negative feedback.
Our Culture
Everything we do is guided by a set of leadership principles that define how we operate:
Patient First. We start with the patient and work backwards. Every decision — what we build, who we partner with, how we operate — is filtered through one question: does this make the patient's life better?
Sense of Urgency. Every day a patient goes unnavigated is a day someone needing help couldn't get the support they needed. We move fast, make decisions with conviction, and carry urgency toward the long-term vision: an AI nurse concierge in every patient's corner.
Ownership. We see things through. We don't ship and walk away — we own outcomes, not just tasks. We act on behalf of the entire company, beyond just our own area of responsibility. We never say "that's not my job."
Insist on the Highest Standards. We hold ourselves and our teams to nothing short of the best — in clinical quality, in operational execution, in how we show up for patients and partners. We raise the bar continuously.
Question Everything, Unapologetically. We reason from first principles, not precedent. We challenge requirements regardless of who set them, dig until we reach the root of the problem, and resist the pull of "that's how it's always been done."
Why Join Us
Mission with massive impact. We're not just improving healthcare — we're transforming patient outcomes at scale. Every system you build puts a dedicated health advocate in someone's corner. We're building one of the largest AI-first companies in healthcare, and this is your chance to own the technical foundation from day one.
Own the AI improvement engine. You won't just build agents — you'll build the system that makes every agent smarter. The eval pipelines, the RL loops, the data flywheel. This is the core of what makes our product defensible.
Learn fast, build fast. We believe in experimentation, measurement, and steady improvement. You'll ship every week, not every quarter.
Grow with us. You'll be part of the team that takes Mira Mace from early product to scale. The decisions you make now will define the company's technical DNA.
Meaningful early equity. This is a full-time role with competitive compensation and real ownership in what we're building.
