Computational Scientist II

Dawar Consulting•South San Francisco, CA

7h•Onsite

About The Position

Our Client, a world leader in Biotechnology is looking for a "Computational Scientist II" for SSF, CA. Job Duration: Long Term Contract (Possibility Of Extension). We are seeking a Computational Scientist II to join 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.

Requirements

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.

Nice To Haves

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.

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.