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 the role
Engram trains models on the knowledge and context that make each customer's work unique. Making that useful in practice means understanding their workflows and solving the last-mile problems that arise when our systems meet real data, code, and users.
We're looking for a Product Engineer - Agents & Harnesses to work closely with our researchers and customers to build, evaluate, and deploy agents that use Engram. You’ll explore how our models behave in real world environments, and solve last mile deployment problems yourself. You’ll turn successful deployments into repeatable approaches and a playbook that help us reach more customers.
What you'll do
Work with researchers to prototype and evaluate workflows that use Engram.
Work directly with customers to understand their workflows, identify useful applications for Engram, and define what a successful deployment looks like.
Develop evaluations with researchers and customers to understand where agents succeed, where they fail, and what changes improve performance
Build integrations and solve last-mile deployment problems across customer data, application code, and our systems.
Own customer issues through resolution: diagnose failures, implement and ship fixes yourself, and verify that they work in the customer's environment.
Build evaluations with customers to measure quality, latency, and cost; use the results to improve deployments alongside our researchers and engineers.
Package successful approaches into reusable agent integrations, evaluation tools, and deployment playbooks that support Engram's distribution.
Your background looks like
A bachelor’s degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field.
Experience building and deploying LLM applications or agents, with an understanding of context management, tool use, and evaluation.
Strong production coding skills, with experience building APIs, data integrations, and reliable backend systems.
Comfort debugging unfamiliar codebases and tracing failures across data, models, and application code.
A track record of owning problems from discovery through implementation, deployment, and validation with users.
Clear communication, whether with customers or researchers – you can translate ambiguous problems into actionable strategy and solutions
Comfort with ambiguity and high ownership at an early-stage company, with the judgment to move quickly and build solutions that last.
Bonus points if you have
Experience in a forward-deployed or customer-facing engineering role.
Experience building agent systems, retrieval pipelines, or evaluation frameworks for real-world workflows.
Experience fine-tuning language models or working with researchers to bring model improvements into production.
Experience as a founder or early engineer, or technical projects you've taken from idea to real users.
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.