AI Architect

Title: AI Architect (Banking AI Platform)

Function

AI/ML Engineering Platform & Foundations Product AI MLOps AI Governance

Experience

5-10 Years

Role Overview

Newgen's AI-first low-code platform powers end-to-end banking journeys including Digital Account Opening, Retail & Commercial Lending, Transaction Banking (Trade & Supply Chain Finance), and Collections.

As an AI Architect, you will lead the design and engineering of enterprise-grade AI and GenAI capabilities embedded within Newgen's banking platform. The role focuses on building production-ready AI services, agentic automation, and intelligent decisioning systems that significantly improve turnaround time (TAT), operational accuracy, risk management, compliance, and cost efficiency across banking workflows.

You will work closely with product, platform engineering, domain experts, and compliance teams to establish scalable and governed AI systems that power the next generation of digital banking.

Key Responsibilities

AI Platform & Architecture

Define and execute the 1224 month AI engineering roadmap for banking solutions including digital onboarding, RLOS, CLOS, trade finance, collections, and wealth management.

Architect multi-tenant AI platforms supporting LLM services, Retrieval-Augmented Generation (RAG), intelligent decisioning, and predictive models.

Design API-first AI services consumable by Newgen banking applications, partner ecosystems, and customer integrations.

AI Decisioning & Risk Intelligence

Build AI-driven decisioning frameworks integrated with LOS/CLOS systems including credit score augmentation models and policy rule alignment using DMN.

Develop explainable AI capabilities for credit decisions.

Develop Early Warning Systems (EWS) for risk monitoring using time-series models.

Document Intelligence for Banking

Architect GenAI-powered document intelligence services including document classification, extraction, summarization, and PII redaction.

Implement OCR and layout-aware models for banking documents.

Build automated trade document validation systems aligned with UCP-600 standards including discrepancy detection and cross-document validation.

Agentic AI & Intelligent Automation

Design agentic AI workflows to automate underwriting assistance, financial spreading, KYC/AML verification, and exception handling.

Implement guardrails such as input/output filters, grounding validation, and policy constraints.

Collections AI

Develop predictive delinquency models, next-best action recommendations, and conversational AI assistants for collections operations.

AI Platform Operations (MLOps / LLMOps)

Establish MLOps and LLMOps frameworks including model registries, embedding registries, CI/CD pipelines, evaluation frameworks, and monitoring.

AI Governance

Define governance standards including PII detection, auditability of AI decisions, retention policies, prompt guardrails, and regulator-ready documentation.

Engineering Leadership

Lead and mentor AI engineering teams including ML engineers, applied scientists, and platform engineers.

Drive best practices in design reviews, reliability engineering, and scalable architecture.

Required Qualifications

1012 years of overall experience with at least 5+ years leading AI/ML engineering teams delivering production AI systems in banking.

Strong expertise in AI system architecture and distributed platforms.

Technical Expertise

LLM architectures, prompting, fine-tuning, and RAG systems.

Decision intelligence and rule engines (DMN).

Streaming data pipelines, vector databases, and feature stores.

Observability, performance monitoring, and AI infrastructure cost optimization.

Document AI Expertise

OCR/ICR pipelines, layout-aware document models, document classification and extraction, trade finance document validation, and KYC/AML document handling.

Banking Domain Expertise

Retail and Commercial Loan Origination Systems (LOS/CLOS), digital onboarding, trade finance operations, supply chain finance, and collections strategies.

Leadership Skills

Strong stakeholder communication skills and the ability to translate AI architecture decisions into measurable business outcomes.

Preferred Qualifications

Experience building AI capabilities in low-code platforms and deploying GenAI solutions in regulated banking environments.

Familiarity with cloud-native AI architectures across AWS, Azure, or hybrid deployments.

Relevant experience in Banking AI projects is considered advantageous.