Bring Your Own Engineering Team

About the role

About Fractional AI How do you turn a decades-old dataset into an industry-leading medical coding agent? Teach an AI receptionist to book appointments in Spanish? Automatically generate working data connectors from API docs? Build agents that write, test, and deploy their own software packages? Fractional AI is focused on putting frontier AI to work. We're a group of veteran Silicon Valley builders who care deeply about getting complex AI systems built right, with strong conviction about what makes them succeed. We're backed by Anthropic, Blackstone, Hellman & Friedman, Goldman Sachs, General Atlantic, Leonard Green & Partners, Apollo Global Management, GIC, and Sequoia Capital. We're headquartered in SF with offices in NYC, Raleigh-Durham, and Dubai. About Bringing Your Own Engineering Team Some teams are just too good to break up. Maybe you co-founded a venture that's pivoting, maybe your team got caught in a reduction in force, or maybe you're looking for the next thing to build together. We already work in small pods: tight-knit teams of engineers working on a single project together. Joining Fractional is a natural way to keep your team intact and shift your focus to building for clients with instant product-market fit. If you're part of an existing team of 2-5 engineers, we encourage you to apply to join Fractional AI together. How It Works One interview process. We'll arrange your interviews on the same day, with the same panel, against the same bar we hold every Fractional engineer to. One offer. If we decide to move forward, we'll make offers to your whole team at the same time. You're each free to accept or decline individually - though we hope you'll all say yes. One first project. We'll work to staff you on an engagement together. BYOT In Practice: Fabius In 2026, we were introduced to the Fabius team - a Y Combinator (W23) startup that had spent three years building AI to automate sales workflows. They had a track record of building complex AI systems, and they'd spent considerable time perfecting the craft of partnering closely with customers to make sure their solutions delivered results. The more we talked, the more we saw a team whose strengths mapped almost exactly to what we hire for. For Fabius, joining Fractional was a natural way to focus on what they were best at - building AI-powered products - while staying together as a team. "I was surprised how much autonomy Fractional expected us to keep. Suddenly we had very interested, very motivated clients - and the same hard technical problems we used to grind through at Fabius. " - Neil Madsen, Fabius Co-founder "When we spoke with Eddie and Chris, it felt like a bunch of founders hanging out. There was a certain expectation that the team itself was an asset, and Fractional was specifically interested in protecting the way we were working together, rather than figuring out how to make everyone play a narrow role." - Andy Day, Fabius Co-founder Who We hire We generally expect your team to fall into the categories of one of our existing engineering and PM roles - most commonly Software Engineer , Senior/Staff Software Engineer or Forward Deployed PM . Take a look at those JDs to see what we look for at the individual level. We evaluate teams holistically on top of that, but we expect every team member to clear a similar bar as all other Fractional team members. Software Engineer Senior / Staff Software Engineer Forward Deployed Product Manager Our Engineering Philosophy We're opinionated about what works in production, and we write about it - from why most eval setups fail by collapsing everything into a single score, to why defaulting to chat interfaces limits AI's impact. We have a distinct approach to building AI systems: applying standard software engineering discipline to the non-deterministic world of frontier AI. We design systems around testable hypotheses, curate durable data sets, and ensure what we ship keeps working long after we've handed it over. After shipping 30+ AI products, we have strong opinions on what makes AI products succeed and how to get them into production. We think you'll find it refreshing if you've seen how most companies approach AI. How Fractional Is Different A typical engineer here ships two to three products per year and learns from dozens more. You have outsized autonomy on each product - but you won't have a year to polish a single system. The upside is constant time on the frontier of models and tooling, and a muscle for AI product development that's hard to build anywhere else. Most engineers look back at this as the biggest growth period of their career. But it's possible you won't like it - we recommend using the interview process to hear what our team thinks. Our Values Overdeliver. We're writing the playbook on how to create enterprise value with LLMs, and building our reputation as the world's best applied AI team. Overuse AI. We go out of our way to experiment with the latest t

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