Senior Software Engineer, Research Biology

GenentechDaly City, CA
9dOnsite

About The Position

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. 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 the CS CoE organisation, the Data and Digital Catalyst (DDC) organization leads the modernization of our computational and data ecosystems by integrating digital technologies across Research and Early Development to empower stakeholders, advance data-driven science and accelerate decision-making. The Solutions team within the DDC Organization develops modernized and interconnected computational and data ecosystems. The Data Ecosystem is foundational to building solutions that accelerate the work done by our Computational and Bench Scientists and enable ML/AI tool creation and adoption. Our team specializes in building Data Pipelines and Applications for data acquisition, collection, storage, transformation, linkage and sharing. We’re looking for a full-stack software engineer to join our team building modern software solutions for Pathology organizations across Roche.

Requirements

  • You have a Bachelor’s or Master’s degree in Computer Science or similar technical field, or equivalent experience and 5+ years of professional experience in a full-stack software development role.
  • You have experience building enterprise-grade systems for R&D scientific data management.
  • You are proficient in programming languages such as Java, Kotlin, and/or Python.
  • You have experience building solutions with NoSQL databases, data warehouses, graph databases, and/or data lakes to store scientific data.
  • You have experience with event-driven architecture patterns and working with streaming platforms such as Apache Kafka.
  • You have experience with front-end frameworks (React, Vue), comfortable with developing APIs and MCPs and experience with Kubernetes for container orchestration.
  • You are proficient with Git, CI/CD tools such as GitHub Actions and Argo, and AWS.
  • You have excellent communication and presentation skills and have experience building solutions on cross-functional teams that include analysts, engineers, product managers, and technical leads.

Nice To Haves

  • Experience deploying systems that include agentic components and low-level orchestration frameworks for agentic workflows such as LangGraph.
  • Experience in a life science or drug development environment is strongly preferred.
  • Knowledge of pathology processes and data is beneficial.

Responsibilities

  • You will develop and maintain systems for collecting, structuring, and storing diverse scientific and operational data that support advanced analytics, machine learning, and other data-driven initiatives.
  • You will deliver data flows and pipelines to support research pathology.
  • You will design and implement integrations between LIMS, ELN, workflow orchestration systems, AWS components, and other internal systems for scientific and operational data management.
  • You will implement novel AI-based solutions (ex. agents) to improve scientific and operational data management.
  • You will be an engineer on a team responsible for working under a technical lead and alongside a team of analysts with deep scientific expertise.
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