Forward-Deployed Engineer - Enterprise; Founding Team

About Fractional AI

Fractional AI builds bespoke software to help organizations solve complex, high-impact problems. Every C‑suite in the country is trying to bridge the gap between AI in theory and AI in practice. We close this gap with exceptional engineering talent and custom end‑to‑end AI builds (see some of our case studies to learn more). By joining Fractional AI, you’re stepping onto a San Francisco, NYC, NC, and Dubai‑based team working on AI projects for top companies from the comfort of an engineering‑first startup.

Fractional AI is launching a new enterprise division, which is physically headquartered in the Triangle of North Carolina. The enterprise division is initially focused on healthcare and life sciences (an area where our leadership team has deep experience), with plans to expand into other industries as we grow. This unique opportunity allows you to be a part of the founding team to help build the division from scratch, but with the stability and resources of an established and profitable startup.

Joining Fractional AI as a Forward‑Deployed Software Engineer, you’ll play a leading role in building and shipping AI applications for our customers – from understanding customer needs to deploying solutions in their environments – all while shaping our engineering and broader Fractional culture for the next 100+ engineers. “Forward‑deployed” means we combine software engineering with customer‑facing problem solving, owning delivery from early scoping through deployment and iteration.

You’ll spend most of your time coding, but close enough to customers to shape the right solution end‑to‑end.

By the time you’ve completed your second project, you’ll have shipped LLM applications across more companies and use cases than the vast majority of AI engineers in the world.

• You write exceptional code + deeply care about the craft of coding (5+ years of experience): you build elegant, production‑ready code; you have strong proficiency across multiple programming languages.
• You are excited about AI. Many strong candidates will be building AI systems for the first time in a production context, so curiosity and learning speed matter more to us than prior buzzword exposure.
• You love solving hard, new problems: you are comfortable self‑teaching, asking “why?,” and experimenting to solve problems you haven’t seen before.
• You thrive in high‑ownership environments: you take initiative, function well with limited structure, and enjoy shaping how work is done. Whether you come from prior start‑up experience or a mature organization, you have owned internal systems, shipped production software, and/or made the transition from data/ML work into scalable engineering.
• You are comfortable talking with users: you deeply care about the user and skillfully navigate user conversations to ensure what we’re building meets their needs.
• You are a great teammate: you are comfortable helping others (and asking for help), you champion integrity in everything, and want to build a one‑in‑a‑career culture of personal growth.

• Design and develop custom AI solutions tailored to the unique needs of our customers, ensuring seamless integration and scalability.
• Partner with a high‑caliber team across the full project lifecycle, from requirements gathering, to prototyping, system design, coding, testing, deployment, and support.
• Actively shape our engineering and broader company culture – from how we learn, to how we hire, to how we celebrate – you’ll shape how we make Fractional a place we all love working.

• We’re generally tech stack agnostic – we work in our customers’ environments and code bases, so we choose tools based on their needs rather than fixed preferences. A lot, but definitely not all, of our work is in Python, Type Script, Vercel, and Terraform.
• After working at Fractional AI for a few years, you’ll become fluent in the modern applied AI stack (e.g., Lang Graph, DSPy, VLLM), from foundation model APIs to evaluation tools (e.g., Braintrust, Pydantic, Inspect
  
  AI), as well as retrieval and deployment frameworks (e.g., Open Pipe, Pinecone, Chroma
  
  DB).