Tiger Analytics Benefits Overview

Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.

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.

Develop and refactor Python optimization algorithms using object-oriented programming for supply chain, inventory allocation, replenishment, and pricing optimization. Build predictive models, apply advanced statistical and optimization techniques to large datasets, and deliver data-driven solutions for retail and CPG clients. Collaborate with business stakeholders and data science teams, communicate analytical insights, coach colleagues, and apply current data science practices to business problems.