Job description

ABOUT CLARION The hardest part of healthcare shouldn’t be getting an appointment. Today, medical staff drown in backlogs of calls, faxes, and scheduling requests. Patients struggle to get the right care at the right time, staff members burn out, and clinics lose billions in revenue. This isn’t a failure of care - it’s a failure of capacity. Clarion exists to solve this problem at scale. Our AI agents handle the patient journey from end-to-end; from scheduling and rescheduling appointments, to managing referrals and prescription refills. Our AI performs complex workflows with a human-like touch that patients love. We’ve raised $10M from Accel, Y Combinator, and Sequoia (Scout), along with founders from Ophelia, Medallion, and Counsel Health. We’re an in-person team based in New York City, moving quickly to ensure every patient gets the care they need. WHY JOIN US? - Solving a real-world challenge: We’re addressing a critical problem that affects millions of patients and providers daily. Our AI agents outperform human schedulers and restore the time needed to focus on patients. - Early-stage with strong market validation: We’ve seen 10x revenue growth in the last year alone. We handle millions of interactions for customers ranging from virtual care clinics to a $5B health insurance company. - Founding team: Our co-founders bring a deep understanding of the healthcare landscape. Our CEO is a Stanford/Harvard-trained physician and clinical ops leader (Two Chairs, Ophelia), and our CTO is an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce. - Outsized early impact: You'll be joining at an early stage where your contributions shape our company's trajectory, processes, and culture, with significant influence on how we grow. - In-person collaboration advantage: We've built in-person since day one and maintain this as a strategic advantage. We move faster, build stronger bonds, and create a cohesive culture. WHAT YOU'LL BE WORKING ON - Build and ship: Write production code—building integrations, configuring AI agents, and implementing platform logic based on customer workflows and scheduling rules. - Own implementations end-to-end: Create and manage technical project plans from scoping through go-live. Coordinate internal resources, delegate workstreams, and drive timelines to completion. - Engineer our moat: Our competitive advantage is our ability to stay in the weeds with customers until the technology works. You will architect the high-leverage systems and playbooks that transform these complex implementations into a repeatable, scalable infrastructure. - Be the technical face to customers: Serve as primary POC for customer technical teams—leading discovery sessions, unblocking integration issues, and building trusted advisor relationships. - Optimize AI agents in production: Monitor agent performance at scale, diagnose failure modes, and iteratively refine behavior to improve accuracy, reliability, and patient experience over time. - Grow accounts: Drive expansion post-launch by deploying new features, identifying upsell opportunities, and proactively solving emerging pain points. - Shape the product: Translate field observations and customer feedback into actionable requirements that inform the product roadmap. REQUIREMENTS - Technical foundation: 3+ years of engineering experience shipping production systems while working directly with customers. This is a hands-on coding role, not purely project management. - Project leadership: Track record of managing complex, multi-workstream technical projects and coordinating cross-functional resources to deliver on time. - Customer-facing presence: Experience as a primary technical POC—comfortable leading architecture discussions and building relationships with technical stakeholders. - Product intuition: Ability to synthesize customer needs into insights that bridge field reality and engineering priorities. INTERESTING TECHNICAL CHALLENGES - AI agent tuning at scale: Configure voice agents for medical terminology and complex scheduling logic, then continuously refine as real-world edge cases emerge in production. - Workflow orchestration: Map and automate multi-step processes—scheduling, insurance verification, prescriptions, documentation—across diverse customer environments. - Personalization that scales: Deploy agents that adapt to each organization's unique protocols and terminology without requiring bespoke rebuilds for every customer. - Debugging AI in the wild: Diagnose agent failures across integrations and LLM behavior, then implement fixes that generalize across deployments. - Shape the product from the field: As the closest touchpoint to customers, identify patterns across deployments and translate insights into product requirements that drive the roadmap. WHAT WE OFFER - Direct mentorship: Work closely with our founding team and experienced leaders who will invest in your professional development - Meaningful equity: Early employee stock options with significant ownership potential - Comprehensive benefits: 100% covered healthcare, flexible time off, commuter benefits, weekly team lunches - Team culture: Quarterly retreats and monthly team events that build genuine connections in our close-knit NYC team - Impact at scale: Work that builds the infrastructure to help millions of patients access care INTERVIEW PROCESS At each stage, we decide within 24hrs and update you shortly after: - First Chat (15 min) [Virtual]: A casual conversation about the role and your experience to see if there's a good initial fit. - Applied Coding Exercise (1 hr) [Virtual]: Hands-on challenge for building and optimizing AI agents in healthcare. - Experience & Culture (30 min) [Virtual]: Deep dive into work style, culture fit, and previous experience. - Onsite (Half-day) [In-Person]: Visit our New York office to meet the team, explore our platform, and solve technical problems collaboratively. If you’re ready to be the customer champion that transforms healthcare communication, we’d love to hear from you.

Requirements

Must-haves

Build and ship: Write production code—building integrations, configuring AI agents, and implementing platform logic based on customer workflows and scheduling rules.
Own implementations end-to-end: Create and manage technical project plans from scoping through go-live. Coordinate internal resources, delegate workstreams, and drive timelines to completion.
Be the technical face to customers: Serve as primary POC for customer technical teams—leading discovery sessions, unblocking integration issues, and building trusted advisor relationships.
Optimize AI agents in production: Monitor agent performance at scale, diagnose failure modes, and iteratively refine behavior to improve accuracy, reliability, and patient experience over time.
Grow accounts: Drive expansion post-launch by deploying new features, identifying upsell opportunities, and proactively solving emerging pain points.
Shape the product: Translate field observations and customer feedback into actionable requirements that inform the product roadmap.
Technical foundation: 3+ years of engineering experience shipping production systems while working directly with customers. This is a hands-on coding role, not purely project management.
Project leadership: Track record of managing complex, multi-workstream technical projects and coordinating cross-functional resources to deliver on time.
Customer-facing presence: Experience as a primary technical POC—comfortable leading architecture discussions and building relationships with technical stakeholders.
Product intuition: Ability to synthesize customer needs into insights that bridge field reality and engineering priorities.
AI agent tuning at scale: Configure voice agents for medical terminology and complex scheduling logic, then continuously refine as real-world edge cases emerge in production.
Workflow orchestration: Map and automate multi-step processes—scheduling, insurance verification, prescriptions, documentation—across diverse customer environments.
Personalization that scales: Deploy agents that adapt to each organization's unique protocols and terminology without requiring bespoke rebuilds for every customer.
Debugging AI in the wild: Diagnose agent failures across integrations and LLM behavior, then implement fixes that generalize across deployments.
Shape the product from the field: As the closest touchpoint to customers, identify patterns across deployments and translate insights into product requirements that drive the roadmap.

Nice-to-haves

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Health Insurance

Professional Development