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Tier-1 bank, metro location and broad GenAI delivery scope increase candidate density despite senior, specialized requirements.
GenAI and LLMOps skills are transferable, but banking Controls domain and enterprise governance increase domain sensitivity.
Multiple explicit years requirements, mandated GenAI/AI/leadership experience, and specific tech stack make filters highly strict.
Lead end-to-end delivery and deployment of Generative AI and agentic AI solutions on enterprise Controls Technology platform.
Manage project lifecycle including ideation, scoping, deployment, and post-launch support ensuring alignment with business objectives and timelines.
Build and mentor AI engineering teams while driving best practices in AI software development, governance, and ethical deployment.
12+ years in engineering, architecture, and implementation with at least 8 years in AI/ML and 3+ years specifically in Generative AI including agentic AI.
5+ years leadership experience managing technical teams and delivering complex AI or software projects.
Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field; PhD preferred.
Extensive hands-on experience with AWS or equivalent cloud services and AI/GenAI infrastructure; strong knowledge of generative AI techniques (context engineering, retrieval systems, knowledge graphs, agent orchestration).
Proven track record delivering enterprise-scale Generative AI and multi-agent system projects, focusing on production-ready solutions leveraging pre-trained foundation models.
Experienced in translating AI strategy into actionable delivery plans within Agile/Scrum frameworks and managing cross-functional stakeholder relationships.
Strong technical expertise in advanced context engineering, retrieval-augmented generation, agent harness design, and AI governance combined with pragmatic problem-solving in fast-paced environments.