Computational Scientist II

About the role

We are seeking a Computational Scientist II to join Genentech's Developmental Sciences organization and help advance AI-driven drug development. In this role, you will design, develop, and deploy LLM-powered agentic workflows that automate scientific processes within Clinical Pharmacology and Pharmacometrics. You will collaborate with scientists, pharmacometricians, and AI engineers to build production-ready AI solutions, develop evaluation frameworks, integrate scientific knowledge into AI systems, and improve the efficiency of quantitative drug development.

Responsibilities

• Design, develop, and deploy LLM-based agentic AI workflows to automate scientific and pharmacometric processes.
• Build RAG (Retrieval-Augmented Generation) pipelines, human-in-the-loop AI systems, and reusable LLM components.
• Develop evaluation frameworks, guardrails, and quality control processes for LLM outputs.
• Collaborate with pharmacometricians, clinical pharmacologists, data scientists, and software engineers to translate scientific requirements into AI solutions.
• Integrate scientific guidelines, templates, and reference documents into AI workflows.
• Develop production-ready software following best engineering practices, including Git, documentation, code reviews, and testing.
• Support deployment of AI applications on cloud platforms (AWS, Azure, or GCP).
• Present technical solutions, documentation, and best practices to cross-functional stakeholders.

Required Qualifications

• Bachelor's degree with 5+ years of experience, or Master's/PhD in Computer Science, Data Science, Bioinformatics, Computational Biology, Pharmaceutical Sciences, or a related quantitative field.
• Experience developing LLM applications, Agentic AI systems, or Generative AI solutions.
• Strong programming experience with Python and software engineering best practices.
• Experience with LangChain, LangGraph, LangSmith, RAG architectures, vector databases, and LLM APIs.
• Knowledge of Git, CI/CD, code reviews, testing, and documentation.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience in pharmaceutical, biotech, computational biology, pharmacometrics, or drug discovery.
• Experience developing AI solutions for scientific or regulated environments.
• Familiarity with evaluation frameworks, LLM guardrails, prompt engineering, and human-in-the-loop workflows.
• Experience working with structured and unstructured scientific data.
• Portfolio of AI/LLM projects or open-source contributions.

Key Skills

• Large Language Models (LLMs)
• Agentic AI & Generative AI
• LangChain, LangGraph, LangSmith
• Retrieval-Augmented Generation (RAG)
• Python Programming
• AI Workflow Automation
• AWS / Azure / GCP
• Computational Biology / Bioinformatics
• Drug Discovery & Pharmaceutical R&D
• Data Science & Machine Learning