Solution Design: Architect scalable GenAI solutions for drug discovery, medical writing automation, clinical trials, regulatory submissions, and real-world evidence generation.
LLM Development & Optimization: Work with data scientists and ML engineers to develop, fine-tune, and optimize large language models (LLMs) for life sciences applications, such as scientific literature analysis, regulatory intelligence, and patient engagement.
AI Infrastructure: Design GenAI solutions leveraging cloud platforms (AWS, Azure, GCP) or on-premises infrastructure while ensuring data security and regulatory compliance.
MLOps & Deployment: Implement best practices for GenAI model deployment, monitoring, and lifecycle management within GxP-compliant environments.
Compliance & Governance: Ensure GenAI solutions comply with regulatory standards (FDA, EMA, GDPR, HIPAA, GxP, 21 CFR Part 11) and adhere to responsible AI principles, including bias mitigation and exploitability.
Performance Optimization: Drive efficiency in generative AI models, ensuring cost optimization and scalability while maintaining data integrity and compliance.
Stakeholder Collaboration: Work with cross-functional teams, including platform teams, engineering teams from various supplier/vendors to align GenAI initiatives with enterprise and industry-specific requirements.
Research & Innovation: Stay updated with the latest advancements in GenAI, multimodal AI, AI agents, and synthetic data generation to incorporate emerging technologies into the company s AI strategy.
Minimum Requirements
Bachelor s or master s degree in computer science, AI, Data Science, Bioinformatics, or a related field.
Experience: 12+ years experience in Big data, AI/ML development with at least 8 years in an AI Architect or GenAI Architect role in pharma, biotech, or life sciences.
Technical Expertise:
Strong proficiency in Generative AI, large language models (LLMs), multimodal AI, and deep learning for pharma applications.
