Benefits

Education

Doctoral degree

Full Job Description

Role Overview We are seeking a highly motivated AI Engineer with 5+ years of experience in Artificial Intelligence, Machine Learning, Generative AI, and Agentic Engineering to join our Pharmacovigilance Technology team. The ideal candidate will work closely with Pharmacovigilance SMEs, Product Owners, Data Scientists, Safety Operations Teams, and Software Engineers to design, develop, and deploy AI-powered solutions that enhance drug safety monitoring, adverse event case processing, signal detection, literature surveillance, regulatory reporting, and medical document intelligence. What You Will Do The role offers an opportunity to shape next-generation AI products leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), NLP, Machine Learning, and Agentic AI frameworks within the Life Sciences domain. Essential duties and responsibilities include AI solution development, data engineering, and deployment of AI models and GenAI applications into production environments. Why It Might Be a Fit The ideal candidate will have experience developing and deploying production-grade AI applications, working with cloud platforms, and production AI/ML deployment environments. Experience working in Healthcare, Life Sciences, Clinical, or Pharmacovigilance domains is preferred. Requirements Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Physics, Bioinformatics, or a related discipline. 5+ years of hands-on experience in AI/ML engineering. Experience developing and deploying production-grade AI applications. Mandatory experience developing solutions using Agentic AI frameworks. Experience with Generative AI, LLMs, RAG, NLP, and AI/ML application development. Experience working with cloud platforms and production AI/ML deployment environments. Experience working in Healthcare, Life Sciences, Clinical, or Pharmacovigilance domains is preferred. Benefits Good understanding of Pharmacovigilance processes such as ICSR intake, case processing, submission, aggregate reports, signal detection, etc. Experience with Graph Databases and GraphRAG. Knowledge of Clinical Trial and Regulatory ecosystems. Experience implementing AI solutions within regulated Healthcare or Life Sciences environments. Experience with AI observability, evaluation, monitoring, and model governance.

Skills and Technologies