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Remote, mid-level GenAI role with popular AI title and 5+ years experience increases applicant competition.
Pharmacovigilance, GxP, and regulatory compliance requirements make the role highly domain-specific and less transferable.
Multiple mandatory technical and domain requirements including 5+ years, Agentic AI frameworks, and Python create strict filters.
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Design, develop, and deploy AI/ML and Generative AI solutions specifically for Pharmacovigilance business processes including drug safety monitoring and adverse event case processing.
Build and optimize Large Language Model (LLM) applications including Retrieval-Augmented Generation (RAG), prompt engineering, AI agents, and workflow automation using Agentic AI frameworks.
Collaborate with stakeholders to integrate pharmacovigilance data sources and ensure AI solutions comply with regulatory and quality standards (GxP, GVP, FDA, EMA, MHRA).
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related discipline; advanced degrees highly valued but not mandatory.
5+ years of hands-on experience in AI/ML engineering with mandatory experience developing solutions using Agentic AI frameworks.
Mandatory technical skills: Python, SQL, REST APIs, Generative AI/LLMs, RAG architectures, prompt engineering, AI/ML deployment on cloud platforms (Azure/OpenAI preferred).
Experience with pharmacovigilance, healthcare, life sciences, or clinical domains preferred; compliance with GxP/GVP and regulatory environment knowledge preferred.
Experienced AI engineer proficient in Generative AI, LLMs, RAG, and Agentic AI frameworks, with a focus on deploying production-grade pharmacovigilance solutions.
Comfortable working cross-functionally with domain experts, product managers, and engineering teams within regulated healthcare or life sciences settings.
Skilled in integrating complex structured and unstructured data pipelines, AI observability, model governance, and operating within GxP-validated environments.