What You'll Do
Frontend (React SPA)
- Build and maintain decision intelligence dashboards spanning the full product surface: financial forecasting, VBC performance tracking, visit optimization, provider benchmarking, capitation reconciliation, population health surveillance, revenue cycle analytics, and contract modeling
- Implement the agentic AI interface: conversational chat with inline data visualizations, autonomous action proposals, attestation blocks, multi-step workflow execution, and real-time status progression
- Build work queue UIs for payment integrity, coding review, and contract variance: flagged items with explainability narratives, confirm/clear workflows, and dollar-impact tracking
- Implement multi-tenant features: organization branding, role-based navigation, parent/child org switching, tenant configuration
- Build report generation and export flows: block-based report editor, PDF/XLSX export, version history, scheduled delivery
- Work with the existing component library to maintain design consistency
- Ensure accessibility compliance (WCAG 2.1 AA) across all new features
- Write serverless handlers for API endpoints: AI agent orchestration, admin operations (tenant provisioning, user invitation, SSO configuration), report generation, data upload
- Integrate with the analytics query layer: wire up frontend query builders, implement tenant security context injection, optimize query patterns for dashboard performance
- Build tenant provisioning workflows: identity provider management, database schema setup, encryption key creation, default configuration seeding
- Implement audit logging: capture all PHI access, mutation, and export events per HIPAA requirements
- Write API integration code for the AI agent: LLM invocation, action group handlers, conversation history management, knowledge base configuration, tool-use orchestration
- Build data upload flows for multiple source systems: claims files, EMR extracts, GL exports, scheduling data, payer remittance, with presigned URLs, progress tracking, ingestion status, and rejection reports
Agentic AI & Infrastructure
- Contribute to the AI agent's capabilities: new action groups, tool definitions, prompt engineering, guardrail configuration, and multi-step workflow orchestration
- Use AI-assisted development tools daily. You're expected to leverage agentic coding assistants, understand prompt engineering, and contribute to an AI-first development culture
- Contribute to infrastructure-as-code: add new serverless functions, API routes, storage resources, IAM policies, monitoring alarms
- Write and maintain CI/CD pipeline steps: type checking, linting, unit tests, infrastructure diffs
What We're Looking For
Required
- 3–5 years of professional software engineering experience
- Solid fundamentals in TypeScript and React: you can build components, manage state, handle async data fetching, and debug rendering issues
- Basic backend experience: writing API handlers, working with databases (SQL), understanding REST APIs
- Comfort with AI-assisted development: you actively use AI coding tools and understand how to work effectively with LLMs
- Familiarity with Git workflows (branching, PRs, code review)
- Willingness to learn cloud services: you should be comfortable reading docs and working with serverless functions, object storage, and API gateways
- Strong communication skills: you'll participate in design discussions and work directly with data engineers and data scientists
- Hands-on experience building with LLMs and agentic patterns (tool use, function calling, RAG), not just calling an API
Preferred
- Experience building with or integrating LLM/AI agent systems (API calls to Claude, GPT, or similar), including multi-step tool use, function calling, retrieval-augmented generation, and human-in-the-loop workflows
- Experience with modern frontend tooling: Vite, Tailwind CSS, component libraries, charting libraries, or similar React ecosystem tools
- Exposure to infrastructure-as-code (CDK, CloudFormation, Terraform, Pulumi)
- Basic understanding of healthcare data concepts (claims, providers, payers, NPI), or genuine interest in learning the domain
- Experience with authentication systems (Cognito, Auth0, Clerk, or similar)
- Experience writing tests (Jest, Vitest, React Testing Library)
- Founding-engineer or early-engineer experience at a venture-backed startup, or Member of Technical Staff at an AI lab: you've shipped 0-to-1 in ambiguity
- Prior time at a healthcare AI company (Tempus, Lightbeam, Lyra, Holmusk, Hinge, Carbon, Devoted, Qventus, Remo, Sprinter, etc.) is a strong plus
- Frontend: React, TypeScript, Vite, Tailwind CSS, component library (shadcn/ui), charting (Recharts), TanStack Query
- Backend: Serverless functions (TypeScript), API Gateway, workflow orchestration
- Auth: Identity provider with PKCE flow and JWT-based authorization
- AI: LLM platform with agentic capabilities (tool use, knowledge bases, workflow orchestration)
- Database: Cloud data warehouse, PostgreSQL
- Storage: Object storage (S3 or equivalent)
- Infrastructure: Infrastructure-as-code (TypeScript), monitoring, IAM, encryption
- CI/CD: GitHub Actions, ESLint, Prettier, Vitest
- Development: AI-assisted coding tools
What You'll Learn
This role is a fast track into healthcare fintech and AI-native product development. Within the first year, you'll gain hands-on experience with:
- Agentic AI systems: building and extending autonomous AI agents with tool use, multi-step reasoning, and human-in-the-loop workflows
- Decision intelligence product design: turning raw data into actionable recommendations across financial, operational, and clinical domains
- Multi-tenant SaaS architecture patterns (schema isolation, RLS, tenant-scoped auth)
- HIPAA compliance engineering (encryption, audit logging, PHI handling)
- Healthcare data models spanning claims, EMR, RCM, GL, scheduling, and public datasets
- Production cloud infrastructure (serverless, workflow orchestration)
Compensation
$145K–$165K base + equity and benefits. Remote, US-based.