Product Engineer, Agents & Harnesses
San Francisco, CAFull-timePosted todayStill listed today
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At a glance
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Job overview
Engram is seeking a Product Engineer - Agents & Harnesses to work with researchers and customers to build, evaluate, and deploy agents using Engram. The role explores model behavior in real-world environments, solves deployment problems, and turns successful deployments into repeatable approaches. The engineer will work across customer workflows, data, application code, and Engram systems, and help improve agent performance and distribution.
Skills & qualifications
Skills
Qualifications
Full 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 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
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Work with researchers to prototype and evaluate workflows that use Engram.
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Work directly with customers to understand their workflows, identify useful applications for Engram, and define what a successful deployment looks like.
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Develop evaluations with researchers and customers to understand where agents succeed, where they fail, and what changes improve performance
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Build integrations and solve last-mile deployment problems across customer data, application code, and our systems.
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Own customer issues through resolution: diagnose failures, implement and ship fixes yourself, and verify that they work in the customer's environment.
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Build evaluations with customers to measure quality, latency, and cost; use the results to improve deployments alongside our researchers and engineers.
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Package successful approaches into reusable agent integrations, evaluation tools, and deployment playbooks that support Engram's distribution.
Your background looks like
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A bachelor’s degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field.
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Experience building and deploying LLM applications or agents, with an understanding of context management, tool use, and evaluation.
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Strong production coding skills, with experience building APIs, data integrations, and reliable backend systems.
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Comfort debugging unfamiliar codebases and tracing failures across data, models, and application code.
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A track record of owning problems from discovery through implementation, deployment, and validation with users.
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Clear communication, whether with customers or researchers – you can translate ambiguous problems into actionable strategy and solutions
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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
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Experience in a forward-deployed or customer-facing engineering role.
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Experience building agent systems, retrieval pipelines, or evaluation frameworks for real-world workflows.
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Experience fine-tuning language models or working with researchers to bring model improvements into production.
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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.
How this job compares
Set against the 1,602 open Product Engineer jobs on Olive Jobs, counted November 12, 2026.
- Pay
- This postingNot listed
- California median$153–250K/yr353 salary ranges
- US median$23–59/hr64 hourly ranges
- Openings
- Olive Jobs lists 460 open Product Engineer jobs in California and 1,602 across the US. 4% of them nationwide are listed as remote or flexible.
- Experience
- Product Engineer postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 7 years (1,303 postings).
- Education
- 544 of the 1,602 open Product Engineer jobs (34%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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