Founding Engineer - Full Stack

The Future of Agentic Buying

People are increasingly trusting AI to help them buy things. First AI agents were information aggregators, trusted to search and summarize. Now they're trusted to advise on key decision-making. Increasingly, they're becoming autonomous buyers: agents that shop, evaluate, and transact on behalf of humans.

When AI is the audience, how it perceives your value proposition becomes one of the most consequential things a company can understand about itself.

Companies starting to take this seriously are realizing something uncomfortable: in an AI-evaluated market, marketing claims without substance to back them up don’t work anymore. Conversely, companies that deliver on their value proposition have unbounded opportunity to reach and acquire new buyers. AI agents are judging every brand's value promise, and are teaching humans how to do the same.

About Unusual

We help companies shape how AI models actually think about their brand and products.

We apply the principles of AI interpretability research to study how models actually think about companies, and underneath the surface noise we find remarkably stable beliefs, formed from the proof points a company has put into the world (often inadvertently).

This is an immensely important and interesting technical challenge – our engineering team focuses on reverse engineering the sources, implicit biases, and reasoning patterns that guide model behavior, and builds products that use this understanding to help people regain control over how they are represented.

From a product perspective, we have a unique opportunity: we can accurately measure LLM’s opinions of a brand, which enables us to quantify a brand’s performance relative to their peers along any dimension. By putting numbers to these previous intangibles, we can add an element of science to the art of brand; perhaps the final piece of a decades-long effort to bring math to marketing.

If you want to define a product category, push the boundary on a new field of research – applied interpretability, and make a positive impact by helping people control their own narrative rather than large AI companies, we’d love to talk.

About the role

As a Founding Engineer, you’ll own problems end-to-end – from high level customer insight all the way to research and infrastructure. You will be expected to understand customer needs, work closely with the executive team, and ship fast.

In addition, you’ll help shape a new engineering team at the dawn of a new kind of software development. Agentic coding is the next paradigm, and as AI tooling improves, we’ll need to work together to regularly reinvent the best patterns and practices for working alongside agents on a team.

Who you are

You are a high-agency builder who thrives on difficult technical problems and wants to own outcomes end-to-end, from customer insight to shipped feature.

You are full-stack, comfortable working from customer-facing UI all the way down to infrastructure.

You are eager to define new ways of operating an engineering team built around agentic coding tools.

You are an individual contributor by choice and want to stay close to the code.

You have a strong sense for product and design that lets you build things people love.

You have prior startup experience or self-driven personal projects that demonstrate initiative.

You are curious about how LLMs work and excited to build systems that probe and influence them.

Bonus

You have scientific research experience.

Bonus

You're comfortable talking to customers directly.

Technical requirements

• 1+ years of experience on engineering teams (3+ preferred)
• Comfortable with React, Python, Terraform, and AWS
• Experience building agentic systems

Who we are

We're backed by Y Combinator and the first investors in SpaceX, Uber, Stripe, Clay, and Notion. And our team has solved some of the most challenging problems in technology and go-to-market—ranging from building the first Starlink prototype at SpaceX to scaling