Founding Engineer

Pear VC•New York, NY

17d•Hybrid

About The Position

The future of medical treatment has arrived, but it’s not evenly distributed. Innovative medical technologies are entering the market every year, but it takes up to a decade for US health insurers to actually cover those treatments for patients (and even longer outside the US), blocking patients from the medical care they need. We are a fast-growing, Stanford-founded early-stage AI SaaS startup (with venture capital funding). We use LLMs and AI agents to fight for medical coverage for individual patients. We have five B2B customers, including one of the largest companies in our customer-space, and a large promising pipeline of prospective customers. Check out our website (demo video at the bottom of the webpage), including About Us and Case Studies.

Requirements

4+ years of software engineering experience (full-stack preferred)
Strong Python and JavaScript/TypeScript skills
Comfort in ambiguous, fast-paced environments; self-starter mindset
Detail-oriented, with a high bar for quality and trust in healthcare tools

Nice To Haves

Startup experience, especially early stage
Experience with LLMs in real-world applications
Familiarity with React, Node, SQL, Docker/Kubernetes

Responsibilities

Feature Development: Design, build, and iterate on end-to-end product features (frontend, backend, or both) using modern frameworks and cloud services.
Execution & Accountability: Turn product goals into scoped milestones, and keep the team unblocked and on-time.
Product collaboration: Work with founders, design, and other engineers to translate user needs into simple, scalable solutions.
Improve our generative AI capabilities. Foundational model training and fine-tuning won’t be necessary, but we do a lot of vertical-specific LLM orchestration.
Team & culture: Raise the bar via code reviews, documentation, and mentoring; help interview future teammates and shape engineering norms.