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Mid-seniority metro ML role with hybrid work attracts moderate candidate competition.
Strong life-sciences regulatory domain requirement limits cross-industry transferability.
Explicit 5–10 years, Azure OpenAI/Copilot and life-sciences regulatory experience makes screening highly strict.
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Lead design, development, and deployment of scalable AI/ML and Generative AI solutions on Microsoft Azure for Life Sciences regulatory processes.
Develop and integrate intelligent AI agents using Microsoft Copilot Studio for regulatory submission management, labeling, quality, and compliance.
Implement AI solutions ensuring compliance with pharmaceutical regulatory standards (GxP, FDA, EMA, ICH) addressing document management, regulatory correspondence, and pharmacovigilance.
5 to 10 years of experience in AI/ML engineering with enterprise solution deployment.
Strong expertise in Microsoft Azure AI Services including Azure OpenAI, Copilot Studio, Cognitive Services, and Azure Machine Learning.
Domain experience in Life Sciences and Pharmaceutical Regulatory Affairs specifically in regulatory submission and compliance.
Location requirement: Hybrid work mode in Hyderabad.
Experienced in developing AI solutions within regulated pharmaceutical or Life Sciences environments.
Familiarity with integrating AI systems with enterprise platforms like SharePoint, Dataverse, and Veeva.
Ability to lead AI governance and mitigate risks such as hallucination in LLM applications in compliance-centric contexts.