Platform Engineer

Engram Lab; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Startup equity

Competitive cash compensation

Job summary

Engram invites a software engineer to join a founding team in San Francisco to build our personalization and continual learning API. You will help architect data infrastructure, power models that learn from context, and work closely with ML researchers and performance engineers.

As a founding hire, you will set engineering standards, participate in code reviews, testing, on-call duties, and help grow the engineering team while collaborating with customers like Notion and Harvey.

Qualifications

• 5+ years of software engineering experience in high-stakes environments.
• Experience building APIs or infrastructure consumed by developers (SDKs, multi-tenant platforms, tooling).
• Taken a product or open-source project from zero to one.
• Product-driven mindset with ability to work across the stack.
• Experience in environments with strong emphasis on security and reliability.

Responsibilities

• Design a secure data storage architecture for raw user context and per-user model weights.
• Build performant systems for data ingest and preprocessing for continual training.
• Develop data observability for quality control and reproducibility.
• Create reliable integrations with customer APIs and data sources.

Skills

API design

SDKs

Multi-tenant

Reliability

Security

Collaboration

Job description

About Engram

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. It rereads your files to answer even basic questions, burns an enormous amount of tokens when sifting through large corpuses, and between sessions, it retains scraps at best.

We train models to study your world and anticipate your questions in advance, forming engrams: compact memories that capture your knowledge and history. Our approach opens a new axis of scaling. 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. Our investors and advisors include Assaf Rappaport, Andrej Karpathy, and Pieter Abbeel.

AI has spent years learning everything about the world. Now it should learn something about yours.

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.

Engram is an equal opportunity employer. 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.