Description

Key Skills: Gen AI, LLM, Forecasting, Prompt Engineering, Data modeling, Vector

Roles and Responsibilities:

• Define the Banking AI engineering roadmap across digital onboarding, RLOS/CLOS, trade finance, collections, and wealth management, prioritized by business outcomes such as TAT, first-time-right, risk, and recovery.
• Architect multi-tenant AI services (LLM/RAG, decisioning, forecasting) with API-first interfaces for Newgen banking apps and partner ecosystems, ensuring features like authentication, tenancy isolation, rate-limiting, and observability.
• Build decisioning and risk services, including credit score augmentation, policy/DMN alignment, explainability, and Early Warning Signals integrated with LOS/CLOS and servicing workflows.
• Develop document intelligence solutions for banking, including GenAI summarization, extraction, and redaction for onboarding and loans, as well as UCP-600 compliant trade checks with auditable trails.
• Operationalize agentic automations for underwriting, financial spreading, KYC/AML, and exception handling with evaluated guardrails.
• Deliver Collections AI solutions, encompassing both data and voice capabilities.
• Establish Banking-grade MLOps/LLMOps, including data contracts, model and embedding registries, and CI/CD processes.
• Own non-functional SLOs such as availability, latency, cost per 1k tokens, throughput, and error budgets; institute golden-path SDKs and reference adapters for rapid solution team adoption.
• Partner with Product, Compliance, and Security teams to codify AI governance, ensuring PII handling, auditability, retention, and regulator-ready documentation.
• Lead and mentor a high-performing engineering team, building hiring plans and coaching for design rigor, reliability, and impact.

Skills Required:

• Expertise in Gen AI, LLMs, and Forecasting models
• Strong skills in Prompt Engineering and AI solution design
• Knowledge of agentic AI workflows and automation
• Experience with data modeling and vector database applications (nice-to-have)
• Hands-on experience in banking AI applications: digital onboarding, trade finance, collections, wealth management
• Knowledge of MLOps/LLMOps, CI/CD, model and embedding registries
• Ability to architect multi-tenant, API-first AI services with security, observability, and scalability
• Experience in credit risk decisioning, document intelligence, and regulatory-compliant AI implementations
• Leadership and mentoring skills for building high-performing engineering teams
• Strong collaboration with Product, Compliance, and Security teams for governance and audit-ready AI solutions

Education: B.Tech

Key Skills

Education

Any Graduate