About this role
Fractional AI is a startup in the heart of Silicon Valley targeting the biggest greenfield opportunity: transforming companies with AI software at scale. Clients include Zapier, Airbyte, and firms from data infrastructure to healthcare. Founded by repeat founders Chris Taylor, Eddie Siegel, and Travis May, backed by Shaper Capital.
This role suits strong software engineers shipping AI products end-to-end across domains with ownership from day one. Work on small teams of 2–5 engineers and a PM, from requirements gathering to deployment. Spend most time in code while gaining client exposure.
Interact frequently with client teams to ensure builds meet needs. Develop domain expertise across AI use cases like medical coding agents and self-deploying software. Join high-caliber engineers, many former founders or staff from Google and Stripe.
Engineers here tackle a decade's worth of hard problems in year one. We're religious about best Applied AI engineering practices. Our philosophy applies software discipline to non-deterministic AI, with opinions on evals and avoiding default chat interfaces.
Requirements
- Experience consistently shipping high visibility or high impact software, with deep care for the craft
- Specific interest in applying software engineering fundamentals to AI systems, balancing frontier models with good design
- Comfort talking with senior technical stakeholders and navigating conversations skillfully
- High ownership mindset: jump in without instruction, embrace no job too big or small
- Low ego, high integrity: help others, ask for help, hold high bar for honesty
Responsibilities
- Ship AI products end-to-end from requirements gathering and prototyping through system design, development, testing, and deployment
- Own features end-to-end across a range of domains
- Develop domain expertise across AI use cases
- Interact frequently with client teams to ensure builds meet needs
- Build agents for medical coding, Spanish-speaking receptionists, data connectors, and self-writing software packages
- Design systems around testable hypotheses and durable datasets
- Ensure shipped products keep working post-handover
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