Phylo - Member of Technical Staff – Product Engineering

deCircle

San Francisco (CA)

On-site

USD 100,000 - 130,000

Full time

14 days+
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Job summary

deCircle is seeking a Product Engineer to develop and scale the core product experiences of Phylo’s AI agent platform in San Francisco. This full-stack, frontend-leaning role will involve building product features, from UI to backend services, and collaborating with scientists and AI researchers. Candidates should have 2+ years of experience, strong skills in modern web frameworks like React and TypeScript, and the ability to work autonomously while maintaining high standards for engineering excellence.

Qualifications

  • 2+ years of industry experience as a product, full-stack, or frontend-leaning software engineer.
  • Strong experience building modern web applications (e.g. React, TypeScript, or similar frameworks).
  • Comfort working across frontend, backend, and infrastructure.

Responsibilities

  • Build and own full-stack product features across the Phylo platform.
  • Design and implement frontend-heavy experiences for interacting with AI agents.
  • Collaborate closely with scientists and engineers to translate capabilities into intuitive product features.

Tools

React
TypeScript

Job description

Phylo is an applied research lab building agentic intelligence to accelerate discovery for every biomedical scientist. We believe AI agents will fundamentally transform how biomedical research is done. Our fast-growing team brings together researchers and engineers across AI and biology.

About the role

We’re looking for a Product Engineer to help build and scale the core product experiences of Phylo’s AI agent platform. This is a highly versatile, full-stack role with a frontend lean, focused on turning cutting-edge agentic research into fast, reliable, and delightful products used by real scientists.

You’ll own product features end-to-end — from UI and interaction design to backend APIs, billing, authentication, and integrations — and work closely with AI researchers, scientists, and infrastructure engineers to ship production-grade systems quickly without sacrificing quality.

This role is deeply interdisciplinary. You’ll spend a lot of time listening, asking questions, and translating between scientists, product, engineering, and AI research. We are an AI-native engineering team: we use coding agents heavily, move fast, and hold a very high bar for engineering excellence.

What You’ll Work On
  • Build and own full-stack product features across the Phylo platform, from user-facing UI to backend services.
  • Design and implement frontend-heavy experiences for interacting with AI agents, workflows, and scientific tools.
  • Own critical product surfaces such as billing, usage tracking, authentication, permissions, and account management.
  • Collaborate closely with scientists, AI researchers, and engineers to translate capabilities into intuitive, production-ready product features.
  • Ship quickly, iterate based on feedback, and continuously raise the bar on product quality, reliability, and performance.
  • 2+ years of industry experience as a product, full-stack, or frontend-leaning software engineer.
  • Strong experience building modern web applications (e.g. React, TypeScript, or similar frameworks).
  • Comfort working across the stack (frontend, backend, and infrastructure) and strong communication skills, with the ability to collaborate effectively across biologists, product, engineering, and AI teams.
  • Strong product instincts — you care deeply about UX, polish, and how real users experience the system.
  • Ability to move fast, own features end-to-end, and operate with high autonomy.
  • High standards for code quality, maintainability, and engineering excellence.
Nice to Have
  • Experience building AI-powered products, agent interfaces, or developer tools.
  • Familiarity with sandboxed or isolated execution environments for agents or user code.
  • Experience with billing systems, metering, or enterprise SaaS features.
  • Experience working in AI-native teams that use coding agents or automation extensively.
  • Interest in scientific, biomedical, or research-focused products.
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