Software Engineer - Full Stack & Agentic AI

About the Role

We're a healthcare technology company building tools that help provider organizations, ACOs, and health systems make better financial and operational decisions. Our platform combines data engineering, analytics, and agentic AI to turn complex healthcare data into actionable intelligence.

As a full-stack engineer, you'll build the frontend experiences, backend services, and AI integrations that tie the platform together. You'll ship features used by healthcare finance and operations leaders — dashboards, work queues, report builders, and conversational AI interfaces.

This is an agentic AI company. You'll build with AI tools daily, ship features powered by AI, and develop fluency in agentic patterns — tool use, multi-step reasoning, retrieval-augmented generation, and human-in-the-loop workflows.

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

Backend (Cloud Serverless)
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:
0–3 years of professional software engineering experience (internships and personal projects count)
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

Preferred:
Experience building with or integrating LLM/AI agent systems (API calls to Claude, GPT, or similar; tool-use patterns; RAG)
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)
Familiarity with agentic AI patterns: multi-step tool use, function calling, retrieval-augmented generation, human-in-the-loop workflows
Experience writing tests (Jest, Vitest, React Testing Library)

Tech Stack
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

Competitive salary commensurate with experience, equity, and benefits.
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