Junior Back-End Software Engineer

As an engineer at Bask you will work directly with the CEO and CTO to build and design the software infrastructure that will serve as the backbone of telehealth.

We are looking to expand our software engineers, seeking those with deep rooted entrepreneurial spirit.

Our serverless platform is a multi-tenant monorepo — Next.js and React on the front, tRPC and Prisma behind it, deployed on SST, TypeScript throughout. One engineer can follow a change from a form field to the database without crossing a team boundary. That's the point.

Engineering at Bask Health is AI-first and builder-led. Work starts with general understanding of problem, moves to tools like Claude and Cursor for further investigation, making a plan and building, tested on staging with realistic data, released to production, tested with real patient and care teams, and then back for systems and polish. AI is a default part of how we work, not a side experiment — because moving fast in healthcare requires every advantage.

We are looking for engineers who take end-to-end ownership, treat AI as a real collaborator, and care deeply about building software that meaningfully improves how healthcare is delivered.

What You'll Do

• Design, build, and ship high-quality product experiences. Own key surfaces end to end, from concept through production. Write elegant, well-tested code — we have a real test suite and we intend to keep it that way.
• Work across the stack. Follow a feature from the interface through the API to the database. No handoffs, no waiting on another team.
• Work AI-first with Cursor and Claude Code. Use LLMs as your starting point. Draft intent, explore implementations, scaffold components, and refactor with AI in the loop. Apply your own judgment to meet the quality bar healthcare demands.
• Prototype fast and validate with real users. Build and test quickly with real patients and care teams. Use what you learn to refine before fully committing — especially in sensitive clinical contexts where getting it right matters.
• Build for scale and own the codebase. Translate product needs into reusable, well-architected patterns that make the next feature faster to ship.
• Make automation legible and trustworthy. Build systems that clearly communicate what AI and automation are doing on behalf of patients and providers. Earn trust through transparency, reliability, and thoughtful defaults.
• Champion performance, accessibility, and reliability. Ship work that is fast, robust, and accessible. Partner across the team to debug, optimize, and raise the bar over time.
• Share AI-native workflows. Document prompts, patterns, and workflows that work, so we move faster together without cutting corners that matter to patient outcomes.