Software Development Engineer/Senior Software Development Engineer, Agentic Systems, AI for Drug Discovery

Genentech•Daly City, CA

2d•$110,200 - $264,700•Hybrid

About The Position

Advances in AI, data and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organizations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The Computational Sciences Center of Excellence (CS CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and life-changing medicines for patients worldwide. Within AI for Drug Discovery, the Software Engineering team builds and operates software platforms that put advanced models and computational tools into the hands of scientists. Our focus is on developing technology and deploying reliable, intuitive solutions that are adopted by users and create measurable impact across drug discovery. We are seeking a very talented Software Development Engineer to help build our agentic platform for molecule design. The platform enables scientists to use AI agents, computational models, scientific tools, and internal data sources together in coordinated workflows that support the design and evaluation of therapeutic molecules. In this role, you will develop production-quality software, integrate scientific and machine learning capabilities, and improve the experience of scientists using the platform. You will collaborate with software engineers, machine learning researchers, computational scientists, product managers, and drug discovery teams across Roche and Genentech.

Requirements

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
For Software Engineer level: 3+ years of professional software engineering experience.
For Senior Software Engineer level: 5+ years of professional software engineering experience.
Proficient in Python and have strong software engineering fundamentals, including API design, automated testing, data modeling, and system design.
Experience independently delivering production software from technical design and implementation through deployment, monitoring, and ongoing support.
Experience building backend services, platform capabilities, developer tools, or user-facing applications in a cloud environment.
Comfortable working with relational databases, asynchronous workflows, containers, version control, and CI/CD practices.
Ability to translate user and scientific needs into practical technical solutions.
Effective communication skills with engineers, researchers, product managers, and domain experts.
Interest in AI-enabled applications and in integrating models, scientific tools, and data into reliable workflows.
Motivated by delivering software to users and improving real scientific workflows.

Nice To Haves

Experience with frontend development using a modern framework such as React.
Familiarity with frameworks and standards for agentic applications, such as Model Context Protocol, workflow orchestration, retrieval systems, or evaluation frameworks.
Experience developing software for scientific research, cheminformatics, computational chemistry, biology, or drug discovery.

Responsibilities

Develop and maintain backend services, APIs, and user-facing applications for an agentic drug design platform.
Integrate machine learning models, scientific applications, databases, and internal services into reliable end-to-end workflows.
Implement agentic capabilities, including tool execution, workflow orchestration, state management, evaluation, and observability.
Build software that enables scientists to configure, run, inspect, and reproduce computational molecule design workflows.
Deploy models and scientific tools into secure, scalable, cloud-based production environments.
Write clean, maintainable, and well-tested code, and contribute to automated testing, documentation, code reviews, and CI/CD practices.
Monitor deployed services, troubleshoot issues, and improve platform reliability, performance, and usability.
Work closely with users to understand scientific needs, gather feedback, and translate requirements into practical software solutions.
Contribute to technical design decisions and the ongoing evolution of the platform’s architecture.
Develop familiarity with relevant drug discovery concepts and apply software engineering best practices in a scientific research environment.