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Strong employer brand, metro location, and mid-level seniority offset by specialized GenAI/LLM skill requirements.
Core ML/LLM skills transfer across industries but pharma/regulatory and supply-chain domain experience increases bias.
Explicit 5+ years plus mandatory GenAI/LLM, LangChain/vector DB, and deployment experience creates strict filters.
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Design, develop, and deploy AI-driven software applications to optimize clinical and commercial supply chain processes.
Own end-to-end AI and data science solutions including prototyping, validation, deployment, and stabilization with measurable outcomes like cycle time and forecast quality.
Collaborate cross-functionally with product, business, technology, and AI teams to translate requirements into scalable, maintainable data-driven solutions integrated into supply chain workflows.
5+ years of experience in AI/ML, Generative AI, analytics, automation, and data visualization for supply chain use cases.
Hands-on development expertise with Python, AI/ML/data science libraries, APIs, SQL/NoSQL, and modern application development.
Experience building GenAI and LLM-based applications including chatbots, Retrieval-Augmented Generation pipelines, vector databases, and AI orchestration frameworks (e.g., LangChain).
Prior exposure to pharma, life sciences, or regulated AI environments preferred; familiarity with GxP, HIPAA, or related compliance a plus.
Strong technical ownership in complex AI and data science projects within supply chain or related domains involving end-to-end delivery.
Experienced in integrating cutting-edge AI technologies such as foundation models and generative AI into enterprise applications with an emphasis on responsible AI and governance.
Comfortable collaborating globally across product, engineering, and business teams to translate business problems into prioritized features and scalable AI solutions within Agile environments.