Senior Software Engineer (Fullstack)

Department: Engineering

Location: NYC Office

Compensation: $150K – $225K • Offers Equity

Employment Type: FullTime

About Clarion

At Clarion, we’re rebuilding how healthcare communicates in the age of AI.

Today, clinics miss 30–40% of patient calls, while staff are overwhelmed by administrative work. We believe AI agents should handle these workflows—scheduling, billing, prescription refills, and follow-ups—so healthcare teams can focus on actual patient care.

We’re building the communication infrastructure modern healthcare needs. Our AI agents don’t just answer calls—they complete workflows end-to-end, ensuring patients never go unheard. To date, we’ve handled hundreds of thousands of patient interactions across virtual care companies, health systems, and a $5B health insurance company.

Clarion was founded by a Stanford/Harvard-trained physician (founding team at Two Chairs and Ophelia) and an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce. We’ve raised $5.4M from Accel, Y Combinator, Sequoia (Scout), and leading healthcare founders. We’re an in-person team in New York, moving fast to solve one of healthcare’s most critical problems.

Why This Role Is Special

• Real traction, early-stage impact: Dozens of paying customers, rapidly growing revenue, and the chance to shape core systems at an inflection point.

• Mission-critical problem: Healthcare communication failures affect millions daily—your work directly improves patient access and outcomes.

• Elite technical context: Work closely with founders who deeply understand both healthcare operations and advanced AI systems, enabling fast decisions and real ownership.

What You’ll Own

• Lead the deployment, performance, and reliability of AI agents operating in live, high-stakes healthcare environments.

• Architect and scale full-stack systems integrating with EHRs, legacy healthcare platforms, and real-time voice infrastructure.

• Drive technical strategy for customer-facing solutions, collaborating with product and engineering to translate client needs into scalable architecture.

• Mentor engineers and set standards for code quality, testing, security, and HIPAA-compliant development.

• Shape product roadmap by identifying systemic challenges in customer workflows and proposing high-leverage technical solutions.

Interesting Technical Challenges

• Generative AI at Scale: Design and operate production systems using LLMs with rigorous safety, alignment, and real-time monitoring at enterprise scale.

• Real-time voice infrastructure: Build ultra-low-latency systems supporting thousands of concurrent calls with 99.99% uptime.

• Fragmented healthcare systems: Design resilient abstraction layers across modern APIs and legacy platforms while maintaining security and compliance.

• Highly Personalized Experiences: Develop adaptive AI that retains patient context across sessions, personalizes tone and flow, and delivers conversations indistinguishable from human care.

What We’re Looking For

• 5+ years of experience designing, building, and scaling production systems in high-reliability environments.

• Strong full-stack expertise with Node.js, TypeScript, React, and PostgreSQL, plus solid system design instincts.

• High ownership and agency—you thrive in ambiguity and take responsibility for outcomes.

• Proven ability to mentor engineers, lead cross-functional efforts, and communicate technical trade-offs clearly.

You’ll be a great fit if you enjoy owning complex systems end-to-end, solving hard problems under real-world constraints, and working closely with customers and teammates to deliver mission-critical software.

Interview Process

We move quickly and communicate clearly at every stage:

• Intro Chat (30 min, Virtual): Background, role context, and leadership philosophy.

• Technical Deep Dive (1 hr, Virtual): System design and architecture with the CTO and a senior engineer.

• Onsite Team Day (Half Day, NYC): Collaborate on real problems, present a past project, meet the team, and assess mutual fit.

Decisions are typically made within 24 hours of each stage.