Senior Full-Stack Engineer

About Longevitix

We're building the platform that helps clinics deliver evidence-based preventative care. We unify data from EHRs, labs, wearables, and lifestyle sources into clear clinical summaries and personalized intervention plans, so clinicians spend less time hunting through fragmented records and more time solving real health problems.

The Role

You'll build the platform end-to-end: frontend, backend, infrastructure, and AI agent integrations. You'll work side-by-side with ML engineers to bring AI capabilities into the product, owning the systems that make it all work reliably at scale.

What You'll Do:

• Build and own full-stack features from concept to production
• Design and implement backend services, APIs, and data pipelines
• Develop frontend interfaces that surface complex health data clearly
• Manage cloud infrastructure (AWS) with security and reliability in mind
• Integrate AI/ML capabilities and agent workflows into the product
• Partner with ML engineers on evaluation, observability, and production-readiness
• Ship fast, iterate quickly, and solve ambiguous problems with minimal hand-holding

Required:

• Strong full-stack experience with TypeScript, Node.js, and React
• Solid backend architecture and API design skills
• Experience with Postgres (schema design, performance, migrations)
• AWS experience (production deployment, security-minded architecture)
• Strong problem-solving abilities, you break down complex problems and deliver working solutions fast
• Comfortable integrating with LLM APIs and AI agent patterns
• Proficient with AI-assisted development tools (e.g. Claude Code, Cursor)
• Thrives in fast-moving startup environments with high ownership and rapid iteration

Our Stack:

TypeScript · Node.js · React · Postgres · AWS · Terraform · Python · AI/LLM APIs and Tools

Bonus Points:

• Python experience
• Terraform / IaC
• Experience building AI agent workflows or LLM-powered features
• Health/regulated-data environments (security, auditability, clinical UX)
• Data unification (normalization, provenance, de-duplication)