Senior Software Engineer, Full Stack (Member Experience)

Suitable for a Senior software engineer with 5+ years of experience owning and delivering production full-stack systems, based in California, Oregon, or Washington and authorized to work without sponsorship.

Required skills include advanced TypeScript, React, Next.js, system design, testing, debugging, code review, GitHub Actions, Vercel deployments, and fluent use of AI development tools, with experience or strong interest in LLM APIs and agentic frameworks.

The candidate should be familiar with building member-facing web applications end to end, designing scalable architectures, integrating AI-powered features, collaborating with product and design, and independently taking work from requirements and pull request through production.

How would you design a full-stack member feature using TypeScript, Next.js, and a backend API?

I would begin by defining the user flow and API contract, then implement the backend domain logic and validation before connecting it to a responsive React interface. I would include typed API clients, loading and error states, automated tests, observability, and a deployment plan.

What are the key considerations when building a production Next.js application for member-facing healthcare workflows?

I would carefully choose between server-side rendering, static generation, and client-side rendering based on data sensitivity, freshness, and performance needs. I would also enforce authorization on the server, avoid exposing protected data to the client unnecessarily, and provide accessible, resilient user experiences.

How would you structure TypeScript types across a React and API-based application?

I would define clear domain models and request and response schemas at the API boundary, using runtime validation in addition to compile-time types. Shared contracts or generated clients can reduce drift, while carefully separating persistence models from public API and UI models improves maintainability.

How would you design an LLM-powered feature for members while protecting accuracy and sensitive healthcare information?

I would constrain the model with approved data sources, structured outputs, clear system instructions, and deterministic business rules for decisions that require correctness. I would minimize and protect personal health information, log safely, evaluate responses with representative cases, and provide escalation or human-readable safeguards when the model is uncertain.

How would you evaluate whether an agentic workflow or framework such as Eve or Strands is appropriate for a feature?

I would use an agentic workflow only when dynamic tool selection or multi-step reasoning provides meaningful value over a deterministic service. I would define explicit tools, permissions, budgets, timeouts, retry behavior, and observability, then compare the approach against a simpler implementation using quality, latency, cost, and operational risk.

What testing strategy would you use for a feature that helps members find care or understand benefits?

I would combine unit tests for domain rules, integration tests for API and database behavior, and component tests for important UI states. Critical member journeys should also have end-to-end tests, including authorization failures, incomplete data, provider errors, and accessibility checks.

How would you design GitHub Actions and Vercel deployments for safe, frequent releases?

Pull requests should run formatting, type checking, linting, unit tests, integration tests, and relevant build validation. Successful changes can deploy to preview environments, while production releases should use protected branches, environment-specific secrets, rollback capability, and post-deployment monitoring.

How do you approach system design tradeoffs between speed to ship, performance, and maintainability in a startup?

I would choose the simplest design that satisfies current requirements while documenting assumptions and clear extension points. I would prioritize high-impact performance work based on measurements, avoid premature abstraction, and isolate change-prone integrations behind well-defined interfaces.

How would you secure a member-facing application that handles health plan and claims information?

I would enforce authentication and authorization on every protected server-side operation, validate all inputs, and use least-privilege access to services and data. I would also protect secrets, apply secure session and cookie settings, audit sensitive actions, avoid leaking information in logs, and use monitoring to detect abnormal access.

How do you use AI tools such as Claude or Cursor in your daily engineering workflow without reducing code quality?

I use AI tools for exploration, test generation, refactoring suggestions, documentation, and debugging, but I remain responsible for design and verification. I review generated code carefully, provide narrowly scoped context, run the full validation suite, and avoid sending confidential data or accepting unverified security-sensitive changes.

Sidecar Health is a mission-driven healthcare technology company transforming U.S. health insurance through more affordable, accessible, and transparent care. As a remote Senior Full Stack Software Engineer on the Member Experience team, you’ll build end-to-end member-facing features, APIs, and AI-powered experiences while partnering with product and design. The stack centers on TypeScript, React, Next.js, LLM APIs, GitHub Actions, and Vercel, with occasional AWS, React Native, and Java; candidates must be based in California, Oregon, or Washington. The salary is $140,000–$185,000 plus bonus, equity, and comprehensive benefits—an excellent opportunity to ship impactful products that help repair a broken healthcare system.