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Strong employer brand and metro location raise interest, but specialized GenAI skillset reduces generalist applicant pool.
Core ML/AI skills transfer across industries, though pharma/regulatory experience increases role fit sensitivity.
Specific GenAI/LLM, LangChain, Python, and regulated-industry familiarity create moderate filtering of candidates.
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Design, develop, and deploy complex AI/ML software applications for clinical and commercial supply chain processes.
Rapidly prototype AI solutions and integrate generative AI models like Large Language Models into supply chain workflows and automation.
Own end-to-end AI/data science projects including problem framing, development, deployment, and measurable impact on operational efficiency and forecast quality.
Experience applying AI/ML and Generative AI including Large Language Models, foundation models, predictive modeling in supply chain contexts.
Proficiency in Python, AI/ML libraries, APIs, SQL/NoSQL, data pipelines, and modern application development.
Hands-on experience with AI orchestration frameworks such as LangChain, LangGraph, or similar tools.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building GenAI and LLM-based applications including chatbots, Retrieval-Augmented Generation, and vector database integration within enterprise applications.
Knowledge of AI agent architectures, orchestration patterns, Responsible AI principles, model validation, and AI governance.
Background or familiarity with pharma, life sciences, or regulated AI environments with understanding of compliance frameworks like GxP or HIPAA.