Engineering Team

Fractional AI builds bespoke gen AI software to transform businesses.

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 and NYC-based team working on gen AI projects for top companies from the comfort of an engineering-first startup.

We get that the right team can be a force multiplier – balancing out our edges and inspiring us to achieve more together. If you’re part of an existing team of 2-5 engineers – maybe you co-founded your own venture and are looking to pivot, maybe your team was impacted by a reduction in force, you-name-it – we encourage you to apply to join Fractional AI as a team.

We’ll arrange your interviews to be on the same day, and If we make an offer, we’ll make it to all of you, at the same time. You’d all be free to accept or decline individually, but of course we’d hope you’d all accept, and then we’d work to find first projects at Fractional AI where you can start working together.

Joining Fractional AI, you’ll play a leading role in building and shipping AI applications for our inaugural customers - from understanding customer needs to deploying solutions in their environments - all while shaping our Engineering and broader Fractional AI culture for the next 100+ engineers.

• You write exceptional code + deeply care about the craft of coding (7+ years of experience): you build elegant, production-ready code; you have strong proficiency across multiple programming languages

• You are excited about AI: you have some demonstrated interest in AI - Whether you've experimented with Lang Chain, built an LLM-based side project, or simply have become a ChatGPT power user

• You love solving hard, new problems: you are comfortable self-teaching, asking “why?,” and experimenting to solve problems you haven’t seen before

• You are ‘start-up ready’: you jump in without instruction, embrace a ‘no job too big, no job too small’ mindset, and want to shape strategy and culture

• 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 lifestyle, 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. A lot, but definitely not all, of our work is in python.

• After working at Fractional AI for a few years, you’ll be an expert at using the various foundational models, building with tools like Langchain/Langsmith, and various other tools and frameworks (e.g., Open Pipe, Pinecone, Chroma
  
  DB).

• You’re the tech lead for one of our customer projects - it may be automating a call center with AI phone agents or building an AI content moderation system – each project is different
  
  You’ll join the team in our SF office between 8am-10am pacific time.

• You’ll dive into one of the higher priority items for the morning (say building out an evals suite). You have a weekly standup with the customer (the CTO at the client) to chat through tradeoffs, progress, and timeline.

• You join team lunch (which doubles as the Fractional AI cross-project standup) to hear about different projects we’re working on … the lunch will turn into a lively debate about Weights and Biases v. Braintrust…