Six Figure Work

Product Engineer, Applied AI

Paradigm

Company websiteparadigm.xyz (Paradigm, opens in new tab)

Base salary $250K  to $400K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceOn-site
  • Status at last checkSource accepting applications when checked
  • Last checked (30 min ago) · observed since

About this job

PRODUCT ENGINEER, APPLIED AI

The Firm

Paradigm is a San Francisco-based investment firm focused on frontier technologies across the globe, with over $11 billion in assets under management. We make investments in companies and protocols at all stages, ranging from early-stage venture financing rounds to growth equity to liquid assets.

Paradigm was co-founded in 2018 and is co-led by Matt Huang and Alana Palmedo. We’ve been hard at work investigating the world’s most beautiful technical problems since day one. Our research-driven approach helps us build relationships with founders and entrepreneurs, but it also reflects our broader goal of accelerating the progress of frontier technology.

The Role

Over the last eight years Paradigm has built some of the most used open-source software in the crypto industry, including Reth and Foundry. Earlier this year we published EVMBench with OpenAI, launched Optimization Arena and hosted the Auto Research hackathon.

More recently, we open-sourced Centaur, a self-hosted runtime for multiplayer AI agents, which we’ve been using to transform how we work at Paradigm and Tempo.

All of these were done part-time by people on Paradigm’s Investing & Research team. This has made us realize that we are people-bound, not idea or impact bound. We need to grow our team to achieve our ambitions.

We want to do three things:

  1. Experiment aggressively. We will push the capabilities of models, harnesses and infrastructure to the limit in service of Paradigm’s broader goals in investing, research, and building.

  2. Build in public. We will get our hands dirty building useful open-source products.

  3. Invest. We will leverage our infrastructure - an area we think is still ripe for disruption with AI - to be better investors. By understanding infrastructure gaps experientially, we may incubate companies that will accrue value by addressing these gaps.

As we deploy more long-running agentic capabilities, we may get into fundamental research, forecasting, model cost optimizations etc., but that is not our focus yet.

We are looking for fearless engineers for this project who understand infrastructure, security, AI models, harnesses, and Slackbots. You will work directly with Georgios, Arjun, Matt Slipper, and the broader Paradigm team, alongside Tempo, and other companies that are themselves operating at the frontier.

Your work will directly impact how Paradigm operates every day. If this sounds like you, reach out.

Responsibilities

  • Build for the people moving the firm: Embed with I&R, Events, and BizOps to find the work and decisions worth automating and ship agents to take it on. The features you build become how the firm sources, researches, and operates, which means your product sense directly shapes how effective Paradigm is.

  • Agent surfaces: Build the user-facing experience, primarily the Slack interface, so collaborating with agents feels fast, legible, and trustworthy.

  • Extensibility and developer experience: Own the systems teams use to extend Centaur without forking it including tools, workflows, skills, and overlays, and make building on top of it feel effortless.

  • Harness integration: Expand support across the different agent CLIs Centaur can run, keeping one clean execution model underneath.

  • Open-source stewardship: As an MIT-licensed project, you're the face of it to the community, triaging issues and PRs, writing the docs and examples, and shaping the guides that pull people in.

Qualifications and Experience

  • A track record of building world-class products

  • Experience applying modern AI and software systems to solve complex, ambiguous problems end-to-end

  • Comfortable navigating everything from foundational models to full-stack product delivery

  • Pragmatic, product-minded builder who cares about solving real problems rather than overfitting to academic ML goals

  • Ability to work autonomously and as a collaborator on the team

Attributes

  • Exceptional team player

  • Extreme open-mindedness

  • Clarity of thought

  • Clear and concise communication (both written and verbal)

  • Technical depth; analytical; rigorous

  • Highly curious; fast learner

  • Ability to bridge technical and investing mindsets

  • Interest in frontier technologies and crypto markets

Source: Paradigm on Ashby · View original posting (opens in new tab)

This range next to 3 other live Paradigm roles with the nearest advertised base floor
Chart as a table
This range next to 3 other live Paradigm roles with the nearest advertised base floor
RolePublished base
Product Engineer, Applied AI (this listing)$250K - $400K
Infrastructure Engineer, Applied AI$250K - $400K
Controller$250K - $350K
Executive Assistant$120K - $160K

Same $100K to $400K scale as every card. All Paradigm roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
  3. fields changed
Observed since
Employer-stated posting date
2026-08-03
Where this pay comes from

Location as the employer wrote it: San Francisco, CA

USD 250,000 – 400,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

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  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.