Principal Backend Architect, AI Platform (Python)

Edison; San Francisco, New York (CA, NY); On-site; USD 175,000 - 240,000; Full time

Benefits offered by this job

Equity

Full healthcare coverage

Parental leave (12 weeks)

Health & wellness benefit

401(k) matching

Commuter benefits

Team off-sites

Job summary

Edison is building an AI-powered scientific discovery platform in San Francisco. We seek a Principal Member of Technical Staff to own backend architecture, design scalable APIs, and develop data pipelines that empower AI agents and researchers.

You will collaborate with frontend engineers, designers, and researchers, mentor senior engineers, and drive reliability and production readiness across services while shipping end-to-end capabilities for science at scale.

Qualifications

• 10+ years in software engineering with backend focus.
• Experience designing and consuming APIs (FastAPI/REST; GraphQL a plus).
• Familiar with databases (SQL/NoSQL) and cloud infra.
• Strong collaboration with frontend, design, and research teams.

Responsibilities

• Define long-term technical architecture for the product platform.
• Lead backend services, APIs, and data pipelines.
• Drive reliability, scalability, and engineering standards.
• Mentor engineers and shape technical strategy.
• Ship AI-driven features in collaboration with teams.

Skills

Backend engineering

Python

API design

Frontend basics

Cloud platforms

Databases

CI/CD

Testing & observability

Tools

FastAPI

REST

GraphQL

React/Next.js

PostgreSQL

MySQL

MongoDB

Docker

Kubernetes

AWS/GCP/Azure

Job description

Edison is building an AI-powered scientific discovery platform in San Francisco. We seek a Principal Member of Technical Staff to own backend architecture, design scalable APIs, and develop data pipelines that empower AI agents and researchers.

You will collaborate with frontend engineers, designers, and researchers, mentor senior engineers, and drive reliability and production readiness across services while shipping end-to-end capabilities for science at scale.