Tiger Analytics Benefits Overview

Leads financial crime compliance business analysis for AML modernization initiatives. Partners with compliance, risk, engineering, and IT teams to define requirements, map banking data, translate regulations into monitoring rules, evaluate vendor capabilities, conduct gap analysis, and manage UAT. Develops BRDs, FSDs, test plans, user stories, and acceptance criteria while supporting transaction monitoring, KYC, sanctions screening, investigations, case management, and regulatory reporting programs.

Designs enterprise-scale data and analytics architectures using Azure, Snowflake, and Databricks. Assesses legacy platforms, develops modernized end-to-end data ecosystems, and establishes data modeling, pipeline, security, governance, privacy, and compliance standards. Partners with senior clients and technology teams to define solutions, lead architecture reviews, guide distributed engineering teams, and drive modernization through automation and reusable frameworks.

Build and deploy production-grade Generative AI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating enterprise data and applications; deploying and scaling cloud-based systems; and optimizing reliability, security, performance, and cost. The role requires direct client engagement, strong software engineering skills, cloud expertise, and hands-on experience with LLM frameworks, agent orchestration, and production AI operations.