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Salary: USD 175,000 - 240,000 / annual
Edison Scientific builds and deploys AI scientist agents to accelerate scientific discovery and the development of new medicines. The company is run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI.
As a Principal Member of Technical Staff, you will help build and support the core platform that automates scientific discovery. This is a full-stack, backend-focused role working primarily in Python. You'll design and build backend services, APIs, and data pipelines while also contributing to user-facing features that make those capabilities accessible and intuitive.
Key responsibilities include:
- Defining long-term technical architecture for the product platform
- Leading the design, implementation, and maintenance of backend services, APIs, and databases powering the scientific discovery platform
- Driving engineering standards, reliability, and scalability across the organization
- Partnering with engineering leadership on technical strategy and roadmap planning
- Mentoring senior engineers and elevating engineering practices across teams
- Building and extending data pipelines that support AI agents and research workflows
- Implementing monitoring, observability, and automated testing to ensure system reliability
- Collaborating with engineering, product, and research teams to ship new AI-driven features
- Growing as a software engineer within a highly collaborative team working at the frontier of AI for science
The role is on-site at the San Francisco office in the Dogpatch neighborhood, described as a converted warehouse with high ceilings and open space.
REQUIREMENTS:
- Typically 10+ years of software engineering experience with exposure to both backend and frontend development
- Strong experience in at least one backend language (Python, Node.js, etc.), with interest in deepening backend expertise; Python required for interview process
- Experience designing and consuming APIs (FastAPI, REST; GraphQL a plus)
- Familiarity with frontend frameworks (React, Next.js, or similar) and modern web development practices
- Working knowledge of relational or document databases (PostgreSQL, MySQL, MongoDB, or similar)
- Exposure to cloud infrastructure (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes a plus)
- Experience with version control, CI/CD pipelines, and basic automated testing
- Strong curiosity, growth mindset, and eagerness to learn in a fast-moving environment
PREFERRED QUALIFICATIONS:
- Experience with data-heavy systems, scientific tooling, or ML/AI-adjacent platforms
- Prior work in startups or small teams with end-to-end ownership
