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Tier-1 bank and metro location amplify competition, but senior GenAI specialization limits generalist applicants.
Requires specialized GenAI/ML expertise plus financial services domain experience, reducing cross-industry portability.
10+ years, mandatory GenAI/LLM stack and financial-services experience enforce strict shortlisting.
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Lead the end-to-end design, development, deployment, and adoption of AI/ML models including Generative AI and Agentic AI to address complex financial reconciliation and data engineering problems at enterprise scale.
Drive ML model lifecycle activities from data preprocessing through validation and production integration, delivering impact across Capital Markets operations, risk, and finance globally.
Collaborate cross-functionally to define model roadmaps, communicate technical findings to senior leaders, and ensure scalable, secure, and reliable performance in production environments.
10+ years hands-on experience in Generative AI/ML development and big data engineering in Financial Services, Insurance, or Telecom domains.
Expert proficiency in Python (scikit-learn, TensorFlow, PyTorch, Pandas, NumPy), SQL, and implementing a broad range of supervised and unsupervised ML algorithms (including neural networks and ensemble methods).
Experience building/deploying Agentic AI and large language model solutions using LangGraph, LangChain, and Agent Development Kit.
Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, Mathematics, Statistics, or related field.
Experienced technical leader comfortable managing complex AI/ML projects bridging advanced data science and financial systems at enterprise scale.
Strong in translating complex data science insights into strategic business recommendations and managing stakeholder communications with senior leadership.
Technically adept in state-of-the-art ML frameworks and tools, with demonstrated ability to deliver autonomous AI agent solutions in production environments.