Senior Backend Engineer

Clarion

New York, New York, United States

New York, New York, United States

Über

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 opportunity to own foundational backend systems at a critical inflection point.
Mission-critical problem: Healthcare communication failures affect millions daily—your work directly powers systems patients and providers rely on.
Elite technical context: Work closely with founders who deeply understand both healthcare operations and large-scale AI systems, enabling fast decisions and real ownership.
What You’ll Own Core backend systems: Design, build, and own the services, data models, and business logic powering Clarion’s AI agents and healthcare workflows.
Workflow orchestration: Build infrastructure for multi-step, asynchronous workflows—including agentic AI workflows with conditional logic, retries, and graceful failure handling.
Healthcare integrations: Own high-stakes integrations with EHRs and legacy healthcare platforms via APIs and RPA.
Platform foundations: Create internal abstractions and tooling that allow the team to deploy and customize AI assistants for new customers quickly and reliably.
Security and compliance: Implement and maintain backend authentication, authorization, and HIPAA-compliant architecture required for enterprise healthcare.
Interesting Technical Challenges Generative AI at Scale: Design and operate production systems using LLMs with real-time monitoring, safety controls, and enterprise reliability.
Agentic workflows: Architect backend systems that coordinate AI agents across complex healthcare workflows with strong guarantees.
Enterprise reliability: Build systems supporting thousands of concurrent patient interactions with high uptime and fast incident detection.
Fragmented healthcare systems: Design resilient abstractions across modern APIs and legacy EHRs while maintaining security and compliance.
What We’re Looking For 5+ years of experience designing, building, and scaling backend systems in high-reliability production environments.
Strong backend expertise across APIs, relational databases, async workflows, and distributed systems .
High ownership and agency—you thrive in ambiguity and take responsibility for system outcomes.
Ability to communicate clearly, collaborate cross-functionally, and surface risks early.
Bonus: experience with security, auth, or regulated environments (HIPAA familiarity is a plus).
You’ll be a great fit if you enjoy owning critical backend systems end-to-end, solving complex problems under real-world constraints, and building infrastructure that directly impacts patient care. Interview Process We move quickly and communicate clearly at every stage: Intro Chat (30 min, Virtual): Background, role context, and mutual fit.
Technical Deep Dive (1 hr, Virtual): Backend systems 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.
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New York, New York, United States

Sprachkenntnisse

English

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