About this role

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. This includes:

• 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). The architecture will be shaped by the constraints and requirements of our R&D work. There are no walls between product, research, and engineering here; delivering on our mission requires a multidisciplinary approach.

This is a founding hire in the truest sense. 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.

Your background looks like

• 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.
• You're product-driven and enjoy working across the stack.
• You've worked somewhere with a rigorous engineering culture, where security and reliability are top priorities.

Bonus points if you have

• Background working with ML teams and familiarity with the modern ML serving and training stack.
• Prior early-stage experience.

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