AI Full-Stack Engineer
US$200,000 – US$350,000 / yr base salary
Posted 4 Sep 2026
Advertised as “Member of Technical Staff, Principal AI Full-Stack Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 10+ yrs
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$200,000 – US$350,000 / yr |
|---|
About Us
Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines. We are an ambitious team run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI.
About the Role
As a Principal Member of Technical Staff (Full-stack, Backend-Focused, Python) you’ll help build and support our core platform that automates scientific discovery. You’ll work across the stack designing and building backend services, APIs, and data pipelines, while also contributing to user-facing features that make those capabilities accessible and intuitive.
Our mission is to build an AI scientist, and you’ll help build the tools, interfaces, and data systems it relies on. While this role leans heavily toward backend engineering, you’ll regularly collaborate with frontend engineers, designers, and researchers to deliver end-to-end functionality.
At Edison Scientific, full-stack engineering isn’t about doing “a little bit of everything.” It’s about owning features from concept to production, understanding how systems fit together, and building reliable foundations that accelerate humanity’s ability to ask bigger questions- and find answers faster.
This position is part of the Platform Engineering team.
Key Responsibilities
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Help define the long-term technical architecture for the product platform.
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Lead the design, implementation, and maintenance of backend services, APIs, and databases that power the scientific discovery platform.
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Drive engineering standards, reliability, and scalability across the organization.
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Partner with engineering leadership on technical strategy and roadmap planning.
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Mentor senior engineers and elevate engineering practices across teams.
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Build and extend data pipelines that support AI agents and research workflows.
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Implement monitoring, observability, and automated testing to ensure system reliability and uptime.
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Collaborate with engineering, product, and research teams to ship new AI-driven features and services.
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Grow as a software engineer within a highly collaborative team working at the frontier of AI for science.
Required Qualifications
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Typically, 10+ years of software engineering experience, with exposure to both backend and frontend development.