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Tier-1 brand and metro location increase applicant volume, but senior LLM banking specialization reduces candidate density.
Requires banking, compliance, and KYC domain knowledge, making cross-industry transfers difficult.
Multiple mandatory filters — years, LLM expertise, banking governance, and secure deployment — raise screening rigor.
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Own end-to-end engineering lifecycle for GenAI and automation in banking operations, including prototype, pilot, production, and support phases.
Design and deliver LLM-powered workflows and AI agent systems integrating securely with enterprise banking platforms and data environments.
Lead stakeholder engagement, define engineering standards, and mentor junior engineers to ensure regulatory-compliant, scalable, and auditable AI solutions.
8-10+ years software/AI/platform engineering or automation delivery experience.
Hands-on with GenAI, NLP, LLM platforms (e.g., Claude, Gemini, OpenAI/Azure), Python programming required.
Bachelor’s or master’s degree in CS, Engineering, Data Science, AI, or related field; equivalent practical experience accepted.
Experience with secure, scalable AI solution design in regulated banking or financial services environments.
Experienced in designing and deploying AI automation solutions specifically for complex banking operations such as KYC, compliance, risk, or reporting.
Capable of high-level stakeholder management, influencing senior business and technical leaders, and leading ambiguity in regulated environments.
Strong engineering leadership with practical expertise in AI model governance, risk management, secure coding, and end-to-end product delivery in financial services.