Product Engineer

San Francisco, CA

About the role

Product Engineer / Product Researcher
At Engram, we're building a new kind of model. Our models build familiarity and deep understanding of the workspaces they operate in, and learn continually over time.
We're hiring for a new role to own this new product experience and be the voice of our customers (application layer AI companies) and the end users that talk to our models.

What you'll do
You'll be one of Engram's first product engineers / product researchers.

Own a product surface end to end, from backend systems to APIs, user experience, deployment, observability, evaluations, and feedback loops
Interface with customers (application layer AI companies) to design models with memory in their products
Develop evals and build telemetry to improve the product experience and the underlying models
Prototype agentic products and interfaces on top of the new kind of models we're building, experiment with shared team-wide agents that know their context, and build internal products to dogfood our technology
Train models to demo product form factors end-to-end, and work closely with model researchers
Help define the product engineering culture, including standards for quality, ambition, and taste

You are:

Entrepreneurial: You may be an ex-founder. You're independent, thrive in ambiguity, love building 0->1, and have an ownership mindset and ability to operate across multiple domains.
Technically rigorous: You understand the technical details deeply, and have solid foundations to build a reliable, high-quality experience for our customers and users. You can communicate with researchers and technical experts outside your domain.
User-centric: You're motivated by building something useful for people, and you listen to customers and users with empathy.
Creative: The models we're building are fundamentally new, and AI as an industry changes week-to-week. You're excited about the greenfield opportunity. You're able to think creatively about how people will use models with memory.
Tinkerer / builder: You're hands-on — you enjoy experimenting with side projects, new products, and agents/AI. You like prototyping and building things. You use agents fluently and have a point of view on how to get the most out of them.

About Engram

Today’s AI models don’t understand what you do. Not really. Everything models know comes from their training – and they’re trained mostly on the public internet. They’re knowledgeable about popular Github repos and things people write in articles online. But what you spend your time thinking about every day is so much more than that. You know what good work looks like. You know where a specific project is going, and where you want it to be in a year. You know everything – from the small details, to the big picture of how life and work fit together – knowledge that goes far beyond any chat window. And when you do write things down, important ideas scatter across a sprawl of documents and files. When you use a model, it reads and re-reads many documents from your company before it can even get started. But as we all know by now, this paradigm isn’t perfect: as our contexts grow, models become more expensive and more confused. Individual users already generate far too much data for a model to process. And reading is shallow and temporary; even when the model does see your context, it forgets everything the moment you close the chat. Right now, models do not learn from this data. This means they can’t automatically get better at the things you use them for. We want to change this by building models that learn from your context. Ours is a fundamentally different bet from other labs. Instead of spending massive amounts of training compute on public data, we start from strong pre-trained models and spend training compute on the context you care about. Each model spends the equivalent of hundreds of years studying your context: piecing things together, drawing connections that have never been drawn, finding errors that went unnoticed.