AI Lead | Retail Banking 70K - 75K

About the role Review business User Requirements (UR) and translate them into actionable AI/GenAI/NLP solutions aligned with credit and loan workflows. Architect and design AI, GenAI, and NLP solutions to automate document processing, credit decisioning, underwriting, and loan drawdown processes. Re-imagine and re-engineer the full loan lifecycle—from application, through underwriting and approval, to final fund drawing—embedding AI agents and automation at each stage. Act as the key liaison between technology teams and business stakeholders, ensuring AI solutions meet operational, risk, and compliance needs while delivering measurable business outcomes. Define a 12–24 month AI engineering roadmap for lending, prioritized by business outcomes (e.g., turnaround time, first-time-right, risk reduction), and oversee model lifecycle management including monitoring, drift detection, and retraining. Key responsibilities Review business User Requirements (UR) and translate them into actionable AI/GenAI/NLP solutions aligned with credit and loan workflows Architect and design AI, GenAI, and NLP solutions to automate document processing, credit decisioning, underwriting, and loan drawdown processes Re-engineer the full loan lifecycle—from application, through underwriting and approval, to final fund drawing—embedding AI agents and automation at each stage Act as the key liaison between technology teams and business stakeholders, ensuring AI solutions meet operational, risk, and compliance needs Define a 12–24 month AI engineering roadmap for lending, prioritized by business outcomes Oversee model lifecycle management including monitoring, drift detection, and retraining About you Deep knowledge of credit workflows, commercial and retail lending, and core banking systems Proven experience working within banking or financial services on lending transformation initiatives Hands-on experience deploying AI solutions—especially NLP, GenAI, and Intelligent Document Processing (IDP)—in finance or banking contexts such as credit scoring, automated underwriting, or document automation Strong capability in UR analysis, functional design, and mapping business requirements to technical AI solutions, including experience with BRDs, FSDs, and user stories Ability to explain complex AI concepts clearly to non-technical business partners, and to collaborate effectively with product, engineering, risk, and operations teams Typically 8–12+ years in banking, consulting, product, or digital transformation roles, with at least 5 years focused on AI/ML or intelligent automation in financial services Experience with RAG pipelines, LLM fine-tuning, and agentic AI workflows in lending or credit contexts Familiarity with loan origination systems (LOS/CLOS), BPM platforms (e.g., Camunda, Pega, Appian), and core banking integrations Understanding of regulatory and compliance requirements in banking AI deployments, including model explainability and auditability