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Tier-1 brand and Bengaluru metro increase applicant density despite senior, niche role.
Requires deep production ML/GenAI, embedded safety expertise and leadership, limiting cross-industry transferability.
PhD preference plus 12-18 years and mandatory production ML/GenAI and safety expertise make filters strict.
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Own and scale AI transformation initiatives focusing on measurable business impacts like revenue, speed, quality, and productivity.
Drive AI use cases from ideation through pilot to production while embedding LLMOps/MLOps standards.
Champion AI-first leadership habits, building maturity models and ensuring governance, responsible AI, and secure deployment across engineering teams.
PhD with AI specialization mandatory.
Strong practical experience in AI/ML/GenAI production environments.
12-18 years of engineering/product delivery experience preferred for fair industry exposure.
Ability to influence senior leadership and drive AI change at scale.
Experienced AI leader with deep knowledge of AI architecture, context engineering, tools, governance, and enterprise deployment.
Proven track record of shipping and scaling production-grade AI solutions affecting cost, quality, and time-to-market.
Operates strategically to embed AI-first culture in engineering and leadership, with focus on safety-critical and enterprise-grade AI implementations.