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Tier-1 employer, metro location, and mid-level GenAI role create high applicant competition.
Core ML/AI skills transfer well, but banking compliance and agentic solution expertise increase domain specificity.
Explicit 4-7 years plus many mandatory tech, MLOps, and compliance requirements produce strict shortlisting.
Lead architecture, design, and development of production-grade Generative AI applications and Agentic solutions for Retail Bank business.
Drive AI initiatives to deepen analytics and build customized solutions enhancing productivity with a focus on generative AI capabilities.
Ensure compliance, security, and performance standards are met while advising business stakeholders and mentoring data scientists in advanced AI solution development.
4-7 years of experience with preferred focus on architecting and developing production-ready Generative AI RAG or Agent-based solutions.
Mastery of Python, AI/ML frameworks (PyTorch, TensorFlow, LangChain), MLOps, and cloud-native architectures (Kubernetes).
Bachelor's degree required; Master's degree preferred in Computer Science, AI, Engineering, or related quantitative field.
Expertise in Agentic solution design, including architecture selection, memory management, hallucination control, reinforcement learning feedback, and compliance/security in production environments.
Experienced in leading scalable and performant technology solution design specifically for generative AI and agentic systems within financial services.
Strong strategic understanding of agent training, performance measurement, and iterative feedback loops critical for AI solution efficacy.
Proven ability to collaborate with stakeholders, mentor technical teams, and influence AI adoption in a business-critical environment.