Backend Engineer

Edison Scientific
San Francisco, CA

About


Edison Scientific focuses on building and commercializing AI agents for science, and shares FutureHouse’s mission to build an AI Scientist - scaling autonomous research, productizing it, and applying it to critical challenges such as drug development.

Role


As a Backend Engineer , you’ll support our core platform that automates scientific discovery. You will design and build data pipelines, APIs, and infrastructure. Our mission is to build an AI scientist, and you’re helping build the tools and data it will use.

By enabling scalable, reliable, and secure backend systems, you’ll be building the foundation that fuels breakthrough science. At FutureHouse, backend engineering isn’t just about servers and databases- it’s about accelerating humanity’s ability to ask bigger questions and find answers faster.

Responsibilities



  • Design, implement, and maintain APIs, services, and databases scientific discovery platform.

  • Implement monitoring, observability, and automated testing to maintain reliability and uptime.

  • Troubleshoot and squash bugs.

  • Collaborate with front-end, design, and research teams to build new AI agents and services.

  • Be a member of a professional software engineer team working at the frontier of AI for science.

Qualifications



  • 4+ years of experience in backend software engineering.

  • High proficiency in one or more backend languages (e.g., Python, Node.js, etc.).

  • Strong experience designing and building APIs (REST, GraphQL).

  • Proficiency in databases (PostgreSQL, MySQL, MongoDB, or similar), with an understanding of schema design and query optimization.

  • Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and containerization/orchestration tools (Docker, Kubernetes).

  • Hands-on experience with CI/CD pipelines, automated testing, and monitoring/observability tools (e.g., Prometheus, Grafana, Datadog).

Bonus points for:



  • Experience with scientific computing, large-scale data pipelines, or ML/AI infrastructure.

Location + Compensation



  • Collaboration is at the heart of discovery. We work on-site to stay close to the science, move faster as a team, and share the kind of energy that only happens when smart, curious people build together- in a space that we love to be in!

    • Location: San Francisco (Dogpatch)



  • At Edison Scientific, we know that titles can cover a range of experience levels. Actual base pay will depend on factors such as skills, experience, and scope of responsibility. Compensation ranges may evolve as we continue to grow. In addition to base pay, team members may be eligible for equity, benefits, and other perks.

    • Compensation: $175,000+


Posted 2025-11-19

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