Software Engineer - Full Stack & Agentic AI

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.

• 3-5 years of professional software engineering experience \n

• Solid fundamentals in TypeScript and React: you can build components, manage state, handle async data fetching, and debug rendering issues \n

• Basic backend experience: writing API handlers, working with databases (SQL), understanding REST APIs \n

• Comfort with AI-assisted development: you actively use AI coding tools and understand how to work effectively with LLMs \n

• Familiarity with Git workflows (branching, PRs, code review) \n

• Willingness to learn cloud services: you should be comfortable reading docs and working with serverless functions, object storage, and API gateways \n

• Strong communication skills: you’ll participate in design discussions and work directly with data engineers and data scientists \n

• Hands-on experience building with LLMs and agentic patterns (tool use, function calling, RAG), not just calling an API \n

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• 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 \n

• 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 \n

• Build work queue UIs for payment integrity, coding review, and contract variance: flagged items with explainability narratives, confirm/clear workflows, and dollar-impact tracking \n

• Implement multi-tenant features: organization branding, role-based navigation, parent/child org switching, tenant configuration \n

• Build report generation and export flows: block-based report editor, PDF/XLSX export, version history, scheduled delivery \n

• Work with the existing component library to maintain design consistency \n

• Ensure accessibility compliance (WCAG 2.1 AA) across all new features \n

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Backend (Cloud Serverless)

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• Write serverless handlers for API endpoints: AI agent orchestration, admin operations (tenant provisioning, user invitation, SSO configuration), report generation, data upload \n

• Integrate with the analytics query layer: wire up frontend query builders, implement tenant security context injection, optimize query patterns for dashboard performance \n

• Build tenant provisioning workflows: identity provider management, database schema setup, encryption key creation, default configuration seeding \n

• Implement audit logging: capture all PHI access, mutation, and export events per HIPAA requirements \n

• Write API integration code for the AI agent: LLM invocation, action group handlers, conversation history management, knowledge base configuration, tool-use orchestration \n

• 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 \n

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Agentic AI & Infrastructure

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• Contribute to the AI agent’s capabilities: new action groups, tool definitions, prompt engineering, guardrail configuration, and multi-step workflow orchestration \n

• 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 \n

• Contribute to infrastructure-as-code: add new serverless functions, API routes, storage resources, IAM policies, monitoring alarms \n

• Write and maintain CI/CD pipeline steps: type checking, linting, unit tests, infrastructure diffs \n

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• 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 \n

• Experience with modern frontend tooling: Vite, Tailwind CSS, component libraries, charting libraries, or similar React ecosystem tools \n

• Exposure to infrastructure-as-code (CDK, CloudFormation, Terraform, Pulumi) \n

• Basic understanding of healthcare data concepts (claims, providers, payers, NPI), or genuine interest in learning the domain \n

• Experience with authentication systems (Cognito, Auth0, Clerk, or similar) \n

• Experience writing tests (Jest, Vitest, React Testing Library) \n

• 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 \n

• Prior time at a healthcare AI company (Tempus, Lightbeam, Lyra, Holmusk, Hinge, Carbon, Devoted, Qventus, Remo, Sprinter, etc.) is a strong plus \n

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Convoy Health is an early-stage, venture-backed healthcare AI company. Small founding team. You’ll own meaningful surface area from day one and ship product into real customer environments within weeks, not quarters. Our platform combines data engineering, analytics, and agentic AI to turn complex healthcare data into actionable intelligence.