Platform Engineering

Today's AI is a brilliant stranger: it can solve the world's hardest math problems, but it knows next to nothing about you and your work. The more we study your context at training time, the better we become at inference time.

We're already working with leaders in AI like Microsoft, Notion, and Harvey, and just raised $98M from General Catalyst, Kleiner Perkins, Sequoia, Factory, Modern, Amplify, Neo and others. AI has spent years learning everything about the world. You'll be one of Engram's first software engineers, joining a team of machine learning researchers and performance engineers in building our personalization and continual learning API, which powers models and agents that learn from user context.

This role will focus on architecting and implementing the data infrastructure underpinning our service. Designing a secure data storage architecture for raw user context and per-user model weights

Developing performant systems for ingesting and preprocessing data on a regular basis for continual training

Building data observability for quality control and reproducibility

Reliable integrations with customer APIs and other data sources

You'll be a major architect of this system, working alongside our researchers and performance engineers within Engram and in deep collaboration with our customers (AI-native application-layer companies like Notion and Harvey). You'll set the bar for engineering at Engram: code review, testing, on-call, and a security posture that gives customers confidence in entrusting us with their most sensitive data. You'll also help build the engineering team around you and influence our engineering culture as we scale.

5+ years of software engineering experience, building and scaling systems in a high-stakes environment.

• Experience building APIs or infrastructure that other developers consume: SDKs, multi-tenant platforms, developer tooling.
• You've taken a successful product or open-source project from zero to one.
• Bonus points if you have

Background working with ML teams and familiarity with the modern ML serving and training stack.

This role is in-person in our SF office. We offer competitive cash compensation and startup equity.

We're building a team that reflects a range of backgrounds and perspectives, and we welcome applicants regardless of race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, or veteran status.