AI Full Stack Engineer

About the role

Help Build the Future of Healthcare AI

Infinitus is AI communications in service of patients.

Healthcare is inherently complex and siloed. We’re pioneering agentic communications to connect the entire system — any stakeholder, any channel, inbound and out. The result is intelligent care that reduces patient anxiety, increases speed to treatment, and enables teams to scale impact without stretching resources.

Our system combines industry-leading safety guardrails with the largest dynamic knowledge graph built on millions of real-world interactions. It’s why 44% of the healthcare Fortune 50 trusts Infinitus to turn fragmented touchpoints into seamless care for better patient outcomes.

The Mission

At Infinitus, our mission is simple: create time for healthcare by making access, adherence, and affordability easier than ever. We’ve automated over 7 million calls and 100M+ minutes of conversation — saving millions of hours for patients and providers.

Backed by over $100M from top investors including Google Ventures, Kleiner Perkins, Andreessen Horowitz, and Coatue, we’re a team that challenges the status quo and moves fast at the intersection of AI and healthcare. Infinitus was recently named to Fast Company's World's Most Innovative Companies and Business Insider’s top startups in healthcare.

YOUR ROLE

We are looking for a senior Fullstack Software Engineer to help us design, build, and scale the core of our digital health platform. You’ll work on expanding the capabilities of Eva, our AI-powered health assistant, and build systems that automate and simplify healthcare administration at scale. This role blends hands-on backend development with opportunities to lead and influence technical direction and mentor teammates.

YOUR IMPACT

- Design, build, and scale AI-powered, user-facing products that make Eva’s healthcare interactions more intelligent, intuitive, and reliable.

- Lead the end-to-end delivery of complex full-stack product experiences, from frontend architecture and backend services to APIs, data integrations, and production workflows.

- Partner closely with Product, Design, Data Science, Infrastructure, and other engineering teams to bring AI capabilities into real user workflows in a practical, scalable, and measurable way.

- Translate ambiguous product and AI opportunities into clear technical plans, balancing speed, user experience, reliability, safety, and long-term maintainability.

- Build robust systems that connect application logic, data pipelines, model outputs, and human-centered product experiences.

- Evaluate and integrate AI technologies, including LLM-enabled workflows, retrieval systems, classification, summarization, automation, and decision-support experiences where appropriate.

- Establish strong frontend and backend engineering standards, including component architecture, API design, system reliability, observability, testing, and development best practices.