Senior Fullstack Engineer (Ambient AI)

Senior Fullstack Engineer (Ambient AI)

Location: Mountain View, CA / San Francisco, CA / Los Angeles, CA (Hybrid, 3 days/week) OR Remote in New York, NY Company Stage of Funding: Late-stage HealthTech scaleup (Series D, $800M+ raised) Office Type: Hybrid / Remote (NY) Salary: $170,000 – $240,000 + Competitive Equity Visa: Visa sponsorship available (H1B transfers, TN, F1 supported; no net-new H1Bs)

Our client is building AI-native healthcare infrastructure designed to simplify clinical workflows and eliminate administrative burden across healthcare systems.

Their platform powers hundreds of care sites, supports over 500,000 clinicians, and processes billions in healthcare transactions annually.

This is an opportunity to join one of the fastest-scaling healthcare AI companies and work on their Ambient AI product — helping clinicians reclaim hours lost to documentation through real-time transcription, clinical note generation, and intelligent workflow automation.

You'll join a high-growth engineering team solving deeply technical challenges at the intersection of distributed systems, real-time AI processing, and healthcare infrastructure.

What You Will Do

Design and influence scalable full-stack architecture for AI-powered healthcare workflows

Build across the stack using Python, Go, TypeScript, and React

Ship production features for ambient clinical documentation systems

Work on real-time transcription reliability and large-scale note generation workflows

Build integrations with clinical systems and EHR infrastructure

Lead technical planning for high-impact product initiatives

Drive system design decisions balancing scale, reliability, and usability

Partner cross-functionally with product, design, and clinical stakeholders

Work directly with customers to solve product issues and improve workflows

Mentor engineers and raise engineering quality standards

Contribute to deployment, testing, observability, and production excellence

Operate effectively in a fast-moving, ambiguity-heavy startup environment

Ideal Candidate Background

5–10 years of full-stack engineering experience

Experience at fast-growing startup or reputable scale-up environments

Strong backend engineering fundamentals with full-stack ownership capability

Experience shipping customer-facing production systems at scale

Strong proficiency in Python or Go

Strong frontend experience with TypeScript and React

Experience with distributed systems and cloud infrastructure

Hands-on system design experience

Experience collaborating directly with customers and stakeholders

Ability to own initiatives from ideation through production

Preferred / Strong Signals

Experience in regulated industries (healthcare, fintech, insurance)

Experience building note-taking, transcription, or workflow automation products

Experience with real-time systems or streaming architectures

AWS / Docker / Kubernetes experience

Cross-platform product experience

Track record of scaling systems through high-growth phases

Technical leadership or mentorship experience

Strong startup adaptability

Top-tier technical education

Strong Signals

Thrives in ambiguity and high-velocity engineering environments

Strong product ownership mindset

Customer empathy and user-centric engineering approach

Ability to move quickly without sacrificing quality

Comfortable shipping frequently

Bias for action

Strong communication across technical and non-technical teams

Genuine interest in healthcare transformation

Compensation and Benefits

Base salary: $170,000 – $240,000

Competitive equity

Hybrid flexibility (3 days onsite)

Remote option in New York

Visa sponsorship support

Work on one of healthcare AI's highest-growth products

Clear growth trajectory in a rapidly scaling engineering org

High-impact ownership

Why Join

This is a chance to work on AI products that solve real, daily pain points for clinicians.

You'll help build ambient clinical intelligence systems that directly improve healthcare delivery while solving genuinely hard engineering problems across real-time AI processing, large-scale infrastructure, and product reliability.

If you want meaningful technical ownership at a company already operating at serious scale — while still moving with startup speed — this is a rare opportunity.