Product Engineer, Applied AI

Paradigm

19h • $250,000 - $400,000 • Onsite

About The Position

Paradigm is seeking fearless engineers for its Applied AI project, focusing on building and deploying long-running agentic capabilities. This role involves experimenting aggressively with models, harnesses, and infrastructure to push the boundaries of AI in service of Paradigm's investing, research, and building goals. The team will build useful open-source products in public and leverage AI infrastructure to enhance investment strategies. The work will directly impact how Paradigm operates daily, with potential future involvement in fundamental research, forecasting, and model cost optimizations. The engineer will work closely with internal teams, Tempo, and other frontier-operating companies.

Requirements

• 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
• 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

Nice To Haves

• Understand infrastructure, security, AI models, harnesses, and Slackbots.

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.

What This Job Offers

• Education Level: No Education Listed