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Tier-1 brand plus metro senior role but specialized leadership role limits generalist applicant competition.
Advanced LLM and enterprise AI leadership skills transfer across industries but regulated-domain experience increases sensitivity.
Explicit senior years, mandatory ML/LLM, cloud, and leadership requirements imply strict candidate filtering.
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Set and drive the enterprise-wide strategic roadmap for AI/ML and generative AI (LLM) aligned with business goals.
Lead design, development, deployment, and lifecycle management of advanced ML, NLP, and generative AI solutions for complex business problems at scale.
Establish frameworks for model governance, validation, explainability, and Responsible AI while building and mentoring high-performing data science teams.
12-17 years overall IT experience, with 8+ years in data science, machine learning, and advanced analytics.
2+ years leading LLM/generative AI solution development and deployment at enterprise scale.
Bachelor’s, BTech, or Master’s in Data Science, Computer Science, Mathematics, Statistics, or related quantitative discipline.
Proficiency in Python, major AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn, Keras), and hands-on experience with LLMs, prompt engineering, embeddings, vector databases, RAG, and cloud AI/ML platforms (Azure/AWS).
Senior leader with proven ability to operationalize large-scale AI/ML and generative AI solutions in complex enterprises.
Technical expertise spanning NLP, LLM architectures, knowledge graphs, model risk management, and MLOps/LLMOps practices.
Experienced in influencing cross-functional teams and senior stakeholders to translate AI strategy into business value and scalable implementations.