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Strong Tier-1 brand and metro location increase candidate density, but senior niche AI specialization reduces competition.
High because deep ML/GenAI expertise, production MLOps, and healthcare governance requirements limit cross-industry transferability.
High due to explicit 15+ years requirement, deep Generative AI/MLOps expertise, leadership and production deployment mandates.
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Lead AI technical strategy, architecture, and solution design for complex enterprise problems using AI/ML, Generative AI, and Agentic AI.
Oversee development of scalable AI solutions from POCs to production readiness, ensuring adoption of reusable frameworks and operational best practices including MLOps.
Lead and mentor a small team of Applied Data Scientists while influencing enterprise AI standards and capability development.
Bachelor's degree in Computer Science, Engineering, Data Science, AI, Mathematics, or related field; Master's preferred.
15+ years of experience delivering enterprise AI/ML solutions, including hands-on Generative and Agentic AI development.
Proficiency in Python, SQL, PyTorch, TensorFlow, and cloud AI platforms (Azure ML, SageMaker, Vertex AI).
Experience leading small technical teams and in AI solution deployment, MLOps, and model governance.
Senior technical leader with proven ability to define and execute enterprise AI strategy across Machine Learning, Deep Learning, and Generative/Agentic AI domains.
Hands-on expert in advanced AI architectures, orchestration frameworks, and scalable production AI systems with prior mentorship and team leadership exposure.
Experienced in navigating complex AI initiatives from experimentation to production, with strategic influence on AI standards and reusable capability development.