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Strong employer brand and metro location increase applicants, but senior GenAI/agentic specialization limits broad competition.
Requires deep LLM and agentic AI expertise, reducing cross-industry transferability.
Strict years, senior leadership expectation, and specialized GenAI/agentic skills make filters stringent.
Develop, pilot, and scale AI solutions specializing in Generative AI and Agentic AI aligned with international AI strategy.
Lead innovation by staying current with advances in generative models, LLMs, and autonomous AI frameworks such as LangGraph, LangFuse, CoT, and ReACT.
Collaborate across teams to integrate AI solutions, ensure code quality, maintain ML Ops pipelines, and translate complex outputs into clear narratives for senior leadership.
Bachelor’s degree with 10-12 years experience or Master’s with 8-10 years in data science or related field.
Minimum 7 years in advanced data science projects including 2-3 years leading data science or ML teams from problem definition to solution.
Proven experience delivering Generative AI and agentic AI solutions, with ability to build and deploy scalable ML models on AWS or Azure cloud platforms.
Mandatory technical skills: strong expertise in LLMs, autonomous AI agents and frameworks, Retrieval-Augmented Generation (RAG), Python programming, deep learning, and production-level ML deployment.
Experienced leader capable of overseeing high-performing data science teams and responsible for end-to-end AI solution delivery.
Expert in cutting-edge generative AI, agentic AI frameworks, and cloud-based ML deployment, with ability to drive innovation and align implementations to strategic goals.
Effective at cross-functional collaboration and translating complex technical AI concepts into actionable insights for senior stakeholders.