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# Staff / Principal Software Engineer

- **Company:** Genbio.AI, Inc.
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Salary:** $250,000 - $350,000
- **Contract:** Permanent contract
- **Skills:** Multitier Architecture, Application Programming Interfaces (APIs), Artificial Intelligence, Business Logic, Computing Platforms, Computational Biology, Databases, Machine Learning, Performance Tuning, Software Engineering, Web Services, Large Language Models, Backend, Front End Software Development, Restful APIs, Model Inference
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/staff-principal-software-engineer-palo-alto-ca--94ce35ee-2cf5-43a2-8c49-33341785d7e3

## About the Role

Software Engineering, Genetics, Scientific Research, Biomedical Research, Bioengineering, Biology, Cell Biology, Drug Discovery, Medical Research, Artificial Intelligence (AI), * Extensive industry experience (typically 8+ years) operating at a Staff or Principal level, with a proven track record of building production web services, scalable APIs, and complex distributed backend systems.

 * Exceptional software engineering fundamentals, demonstrating a mastery of clean architecture, modular system design, and the ability to write highly maintainable, performant code.
 * Deep, hands-on experience integrating large-scale AI, LLMs, or machine learning inference systems into highly available production environments.
 * Proven ability to solve challenging, ambiguous systems problems from the ground up, moving from concept to scalable execution.
 * Outstanding cross-functional communication and leadership skills, with the ability to bridge the gap between deeply technical engineering teams, AI researchers, and scientific product teams., * Domain knowledge or prior experience working with computational biology, genomics, transcriptomics, protein/molecular structures, healthcare, or scientific software.
 * Familiarity with building tools for scientific simulation, automated laboratory experiment management, or complex workflow orchestration.
 * Experience building unified computational frameworks (similar to our AIDO Foundry) that accelerate the development and deployment of AI-native platforms.

## Description

GenBio AI is an AI for Science company on a mission to make biology fully computable. We are building AIDO (AI-Driven Digital Organism) to simulate living systems, decode biology holistically, and accelerate medical and scientific research. Our first step toward that mission is AIDO Cell, the first virtual cell world model that holistically simulates cell biology from molecules up to whole-cell behavior. It enables researchers to run experiments virtually, predicting how cells respond to genetic changes, drugs and other interventions before going into the lab. It is supported by AIDO Foundry, an AI-builds-AI engineering framework for automating virtual cell development, and AIDO Lab, an interface to digitally run experiments and observe the results. Together they form the foundation for a new paradigm in AI-driven drug discovery, bioengineering, and fundamental biomedical research., We are seeking an experienced Staff to Principal-level Software Engineer to build the user-facing platform that brings these capabilities to computational biologists, experimental scientists, and pharmaceutical researchers. This is a senior individual contributor role for engineers who enjoy solving challenging systems problems while working closely with AI researchers and product teams., * Act as a senior technical leader to build the software platform for programmable biology, developing production-grade backend services and APIs for our Virtual Cell products.

 * Design clean, robust interfaces that seamlessly connect frontend applications, core business logic, massive biological databases, and state-of-the-art AI inference engines.
 * Architect and develop highly scalable systems for complex biological simulations, experiment management, workflow orchestration, and the processing of multimodal biological data.
 * Drive continuous improvements in platform performance and reliability through highly efficient architecture design, strategic caching, asynchronous execution, and optimized distributed infrastructure.
 * Collaborate closely with AI researchers to translate cutting-edge foundation models into reliable, user-facing scientific products that enable virtual perturbations and hypothesis generation.
 * Work cross-functionally across frontend, backend, infrastructure, and machine learning teams to deliver deeply intuitive computational experiences for biologists, experimental scientists, and pharmaceutical researchers.