Tiger Analytics Benefits Overview

Leads client-facing AI and Generative AI engagements from discovery through production while combining project leadership with hands-on engineering. Responsibilities include architecting and deploying LLM applications, RAG systems, AI agents, and production AI services; coordinating technical teams; managing delivery risks and timelines; and translating business needs into practical AI solutions. The role requires expertise in Python, cloud platforms, LLM frameworks, vector databases, APIs, microservices, deployment, evaluation, monitoring, and responsible AI.

Leads technology advisory, client engagement, presales, solution architecture, and practice development for enterprise data and AI transformations. Provides thought leadership, assesses client platforms, develops modernization roadmaps, creates architectures and proposals, and mentors engineering, data, and architecture teams. Requires deep hands-on Databricks and Azure expertise, experience with enterprise Lakehouse platforms, streaming and batch pipelines, governance, security, and large-scale transformation programs. Partners with senior executives and offshore teams to drive delivery quality, talent development, and consulting growth.

Designs and deploys advanced AI and machine learning solutions, including AI agents, RAG systems, analytical models, and data products on Google Cloud Platform. Responsibilities include preparing structured and unstructured data, developing AI agent tools, applying NLP and deep learning, collaborating with customers and stakeholders, generating business insights, and communicating analytical results.