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Tier-1 brand and Bangalore metro presence increase competition, though seniority and niche AI governance reduce density.
Strong banking operations, regulatory and controls context makes cross-industry transferability limited.
Requires senior production ML experience, bank governance knowledge, and leadership, so filters will be strict.
Lead the design, development, and implementation of AI solutions to improve Corporate Banking and Investment Banking Operations and Controls, targeting efficiency, cost savings, and revenue growth.
Manage and develop a Data Science and AI Engineering team, fostering adoption of AI best practices across CBIBOC and Deutsche Bank globally.
Ensure AI governance compliance, prioritize AI use cases based on ROI and risk, and track key performance indicators for deployed solutions.
Demonstrable experience deploying classical Machine Learning and advanced AI solutions in a tier-1 or G-SIB bank, preferably in Operations or Control functions.
Proficiency with AI developer tools (e.g. PyTorch, TensorFlow, scikit-learn), no-code/low-code AI platforms, and modern data solutions like BigQuery, Looker, Snowflake.
Ability to write and review Python code; experience with production-grade software development under SDLC frameworks.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced leader capable of balancing hands-on AI development, team management, and governance responsibilities within a global banking environment.
Strong stakeholder management skills with the ability to translate business needs into scalable AI solutions and communicate effectively across technical and non-technical teams.
Deep expertise in AI risk management, AI solution lifecycle control, and current AI trends especially within cloud platforms like Google Cloud.