AI Full Stack Engineer
Infinitus Systems5 months ago
Responsibilities
- Design, build, and scale AI-powered user-facing products for Eva’s healthcare interactions.
- Lead end-to-end full-stack product delivery spanning frontend architecture, backend services, APIs, data integrations, and production workflows.
- Partner with Product, Design, Data Science, Infrastructure, and engineering teams to integrate AI into practical user workflows.
- Translate ambiguous product and AI opportunities into clear technical plans and make tradeoffs involving user experience, reliability, safety, scalability, and maintainability.
- Build systems connecting application logic, data pipelines, model outputs, and product experiences.
- Evaluate and integrate LLM-enabled workflows, retrieval systems, classification, summarization, automation, and decision-support capabilities.
- Establish frontend and backend standards for component architecture, API design, reliability, observability, testing, and development practices.
- Drive technical alignment across teams and organizations to ship high-impact work.
- Mentor and grow engineers while contributing to technical roadmaps for AI-enabled product development, platform scalability, and full-stack architecture.
- Help shape responsible, useful, trustworthy, and reliable applications of AI in healthcare workflows.
Requirements
- 8+ years of practical full-stack engineering experience.
- Track record of leading complex consumer or B2B user-facing products across the full stack.
- Deep proficiency in modern frontend and backend development using technologies such as React, TypeScript, Python, Go, Java, C++, or similar.
- Experience designing scalable APIs, backend services, data models, integrations, and distributed systems.
- Hands-on experience with cloud infrastructure and modern DevOps practices, ideally across AWS, GCP, or similar environments.
- Experience with SQL and NoSQL database systems, including performance, reliability, and scale optimization.
- Practical experience with AI-enabled product development, including LLM integrations, model orchestration, prompt and system design, retrieval-augmented generation, evaluation workflows, or AI-assisted automation.
- Strong product judgment and a user-centered approach to building robust, scalable, trustworthy, and usable solutions.
- Experience in early-stage startups or similarly fast-moving environments, ideally building products from 0 to 1.
- Ability to navigate ambiguity, define technical direction, deliver high-quality products, and drive cross-team alignment.
- Experience establishing engineering standards, component architectures, reusable patterns, and development best practices.
- Demonstrated mentorship mindset and commitment to developing peers and junior engineers.
- Entrepreneurial ownership and ability to drive projects from concept through production impact.
- Preferred: experience building AI-powered products in healthcare, fintech, enterprise SaaS, or other high-trust domains.
- Preferred: experience with evaluation, monitoring, and reliability practices for production AI systems.
- Preferred: familiarity with healthcare data, clinical workflows, privacy-sensitive systems, or regulated environments.
- Preferred: experience building internal platforms or tooling that accelerate AI product development.
Benefits
- Hybrid work for Bay Area positions, with SF office days Monday, Tuesday, and Thursday
- Catered lunches for Bay Area positions
- 401(k) and medical, dental, and vision benefits
- Wellness stipend
- Generous paid time off and parental leave
- Bi-annual offsites and a collaborative, mission-driven culture
Categories
About Infinitus Systems
Infinitus Systems builds voice AI agents that automate phone-based healthcare workflows such as benefit verification and prior authorization for pharma manufacturers, health plans, and provider networks. The company sells an enterprise platform and APIs used to coordinate access, adherence, and affordability, and reports automating 7M+ calls and 100M+ minutes. Founded in 2019 and headquartered in San Francisco, it is privately held with investors including GV, Kleiner Perkins, Andreessen Horowitz, and Coatue.