AI Full Stack Engineer

Infinitus Systems•San Francisco, CA

1d•Hybrid

About The Position

Infinitus is pioneering agentic communications to connect the entire healthcare system, leveraging AI to reduce patient anxiety, increase speed to treatment, and enable teams to scale impact. Their system combines safety guardrails with a large dynamic knowledge graph, trusted by 44% of the healthcare Fortune 50. The company's mission is to create time for healthcare by simplifying access, adherence, and affordability, having automated over 7 million calls and 100M+ minutes of conversation. Backed by significant investment, Infinitus is recognized for its innovation at the intersection of AI and healthcare.

Requirements

8+ years of practical full-stack engineering experience
A track record of leading the design and delivery of complex consumer or B2B user-facing products across the full stack.
Deep expertise in modern frontend and backend development, with strong proficiency in technologies such as React, TypeScript, Python, Go, Java, C++, or similar.
Strong 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.
Solid understanding of database technologies, including SQL and NoSQL systems, with experience optimizing for performance, reliability, and scale.
Practical familiarity with AI-enabled product development, such as LLM integrations, model orchestration, prompt/system design, retrieval-augmented generation, evaluation workflows, or AI-assisted automation.
Strong product judgment and a user-centered approach to building solutions that are robust, scalable, trustworthy, and easy to use.
Experience working in early-stage startups or similarly fast-moving, rapidly evolving environments; ideally, you have built products from 0 to 1.
Ability to navigate ambiguity, define technical direction, and deliver high-quality products in fast-paced environments.
Demonstrated success driving cross-team or cross-org alignment to get impactful work shipped.
Experience establishing engineering standards, component architectures, reusable patterns, and development best practices.
A strong mentorship mindset and a deep commitment to investing in the growth of peers and more junior engineers.
Entrepreneurial mindset: you take initiative, operate with ownership, and drive projects from concept through production impact.

Nice To Haves

Experience building AI-powered products in healthcare, fintech, enterprise SaaS, or other high-trust domains.
Experience with evaluation, monitoring, and reliability practices for AI systems in production.
Familiarity with healthcare data, clinical workflows, privacy-sensitive systems, or regulated environments.
Experience building internal platforms or tooling that accelerate AI product development across engineering teams.

Responsibilities

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.
Make high-quality technical tradeoffs across product impact, engineering complexity, scalability, and long-term platform health.
Drive cross-team and cross-org alignment to ship high-impact work, influencing through technical clarity, judgment, and collaboration rather than authority.
Mentor and grow engineers across the team, raising the bar for technical execution, product thinking, and engineering culture.
Contribute to both short- and long-term technical roadmaps, especially around AI-enabled product development, platform scalability, and full-stack architecture.
Help shape how Eva responsibly applies AI in healthcare workflows, with a focus on usefulness, trust, reliability, and excellent user experience.