Mira Mace — Senior AI Engineer, Voice Systems

Type: Full-time | Remote (US), preference for San Francisco or Boston | San Francisco, CA Compensation: $180K–$220K + competitive equity Hiring count: 1 Visa sponsorship: Open to visa transfers (e.g. OPT, H-1B transfers) Reports to: Abhinav Garg, Head of Engineering

About Mira Mace

Mira Mace pairs Medicare beneficiaries with a dedicated healthcare advocate who navigates appointments, insurance, and care coordination on their behalf — nurses provide the human touch while AI agents handle the tedious backend work, all covered by Medicare. The long-term vision is an AI nurse concierge that makes 24/7 personalized health assistance affordable for everyone, not just the rich or the acutely ill.

Founded: 2025 | Team size: 9 | Total funding: $6.5M Industry: Healthcare, AI Website: www.miramace.com Office: Boston (relocating to San Francisco) Backing: Foundation Capital, DefineVC, and top Silicon Valley angels

Why Candidates Should Join

• $1M ARR in under a year: Rapid growth across multiple channels (direct-to-consumer plus B2B referrals from hospitals, insurers, and PCPs), venture-backed by Foundation Capital, DefineVC, and top Silicon Valley angels.
• Voice is the product, not a feature: Phone conversations are how the work gets done in healthcare — you own the core capability of the company, not a side project.
• Strong founding team: Google, Meta, Dropbox, and Amazon backgrounds with serial startup experience ranging from bootstrapped ventures to Series D scale-ups.
• Real moats being built: Reinforcement learning from real nurse interactions, plus local network effects (hospital pharmacy equipment vendor) that compound zip code by zip code, similar to Uber's city-level defensibility.
• Comp and ownership: Competitive comp ($180K–$220K) plus meaningful early equity, remote-friendly (US) or hybrid in SF/Boston, on a ~9-person team where your decisions define the company's technical DNA.

Intake Call Summary

• Care navigation for Medicare beneficiaries, with a vision of an AI nurse concierge; venture-backed, ~1 year old, at roughly a $1M run-rate revenue.
• Team of 9 full-time employees — 2 in Boston, the rest distributed across the US; planning to relocate to San Francisco soon.
• Hiring a Senior AI Engineer focused on reinforcement learning, voice, and agentic systems; core work is automating tasks nurses currently do manually and improving AI accuracy.
• Open to candidates with 1–3 years of experience, including recent graduates with demonstrated excellence; rapid-learning ability weighted over specific stack experience.
• Open to remote candidates, but preference for Boston or San Francisco.
• Ideal profile shows demonstrated excellence (top university or significant achievement) and thrives in unstructured, early-stage environments.
• Wants to raise the quality of AI automation to reduce reliance on human advocates.
• Compensation discussed on the call: $200K–$240K, with flexibility for the ideal candidate — note this differs from the $180K–$220K posted salary range (see Source Inconsistencies).

The Role

Own and improve the agentic systems that automate healthcare-navigation tasks on behalf of patients — building the "cursor for nurses": automating outbound voice calls, agentic search, and multi-agent orchestration, using reinforcement learning from real nurse interactions to continuously improve quality.

What You'll Be Doing

• Automating tasks that healthcare advocates currently do manually — outbound voice calls to insurance, doctors, pharmacies, and patients
• Building and improving agentic search and multi-agent orchestration systems that coordinate across complex healthcare workflows
• Designing evaluation infrastructure to measure and improve the quality of AI automations so advocates increasingly rely on them
• Implementing reinforcement learning loops that use real nurse actions to train and improve models over time
• Shipping fast and iterating directly with the team that listens to real conversations daily

Tech stack: Streaming STT/TTS, telephony (Twilio/SIP), multi-agent orchestration, RAG, reinforcement learning (inferred from the Hard Skills requirements — not stated as an explicit stack in the source).

Qualifications

Seniority

• 1–10 years of experience in AI/ML engineering, building systems including voice AI [Required] (see Source Inconsistencies — intake call and role description both say 1–3 years)

Work Experience

• Has shipped voice AI to production [Must have]
• Shows some kind of excellence in their experience (worked at a growing startup [Series A–D], shipped major products, raised funding, olympiad, etc.) [Required]
• Ex-YC founder, or from stalling later-stage companies (e.g. Eightfold AI), or Big Tech with prior startup experience [Strongly preferred]

Education

• Undergraduate degree in CS from a top 25 university in the US or Canada [Must have] (role description states this more loosely as "top university" — see Source Inconsistencies)

Hard Skills

• Production voice AI stack — streaming STT/TTS, telephony (Twilio/SIP), latency optimization, endpointing [Required]
• Agentic systems — context engineering, multi-agent orchestration, tool use, RAG [Required]
• Built evaluation pipelines for voice systems — metrics, regression suites, production signal [Strongly preferred]

Soft Skills

• Rapid learner who thrives in ambiguity — builds the playbook rather than following one [Required]

Miscellaneous

• Willing to relocate to SF Q1 2027 [Required] (tension with "remote open for strong candidates" — see Source Inconsistencies)

Traits to Avoid

• None specified in source (no "Traits to Avoid" markers present in the HTML).

Role Details

• Salary: $180K–$220K (posted); $200K–$240K discussed on intake call
• Equity: Competitive (early-stage equity; % not specified)
• On-site policy: Remote (US); preference for SF or Boston; relocation to SF expected Q1 2027 per the Miscellaneous requirement
• Visa sponsorship: Open to visa transfers (e.g. OPT, H-1B transfers)
• Employment type: Full-time
• Location: San Francisco, CA / Remote (US)

Candidate Questions (Paraform submission form)

1. What's one thing in your life where you've demonstrated peak excellence, whether it's academic, professional, athletic, or something else entirely?
2. Describe a production AI agent or voice AI system you've built end-to-end. What was the hardest part of getting it to work reliably in the real world?
3. Are you able to work on-site in San Francisco or Boston, or are you looking for a fully remote role?

Scorecard (Paraform submission form)

Yes/No per item. Priority labels carried from the JD qualifications.

• Has shipped voice AI to production [Must have]
• Undergraduate degree in CS from a top-25 university in the US or Canada [Must have]
• 1–10 years of experience in AI/ML engineering, building systems including voice AI [Required]
• Shows some kind of excellence in their experience (growing startup [Series A–D], shipped major products, raised funding, olympiad, etc.) [Required]
• Production voice AI stack — streaming STT/TTS, telephony (Twilio/SIP), latency optimization, endpointing [Required]
• Agentic systems — context engineering, multi-agent orchestration, tool use, RAG [Required]
• Rapid learner who thrives in ambiguity — builds the playbook rather than following one [Required]
• Willing to relocate to SF Q1 2027 [Required]
• Ex-YC founder, or from stalling later-stage companies (e.g. Eightfold AI), or Big Tech with prior startup experience [Strongly preferred]
• Built evaluation pipelines for voice systems — metrics, regression suites, production signal [Strongly preferred]

Overall rating (maps to score vs internal JD): Poor fit (<60) · Ok fit (60–74) · Good fit (75–84) · Excellent fit (85+)

Interview Process

Not available — the interview process ("3 steps") was collapsed in the copied HTML. Expand and re-copy to capture the stages.

Stage 1 — TBD Stage 2 — TBD Stage 3 — TBD

Offer Extended

Candidate Hired

Ideal Companies & Backgrounds

No dedicated "Ideal Companies" section was present in the source. The only company signals are: Eightfold AI (named as a "stalling later-stage" example), and founding-team pedigree from Google, Meta, Dropbox, and Amazon. If there is a fuller Ideal Companies list on the page, please supply it — I have not fabricated one.

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

Luke (Muwei) G. — LinkedIn AI Software Engineer | Greater Seattle Area

• Rapid career progression — promoted every year, reaching Staff level quickly
• Attended McGill (competitive school) and Harvard for master's
• Worked at Supio, a legal AI startup — relevant agentic/AI experience at an early-stage company
• Trajectory signals high performance

Areas for improvement (per source): Seattle-based and looking for remote (may need location flexibility); $200K–$240K expectation may be at the higher end; reason for leaving Supio unclear.

Note: a "View all profiles" link was present — additional example profiles may exist that were not expanded in the copied HTML.