Teams at Tiger Analytics

Lead enterprise data modernization by designing canonical and semantic data models, data contracts, and real-time streaming architectures (Kafka). Architect AWS and Snowflake-based pipelines, enforce governance and metadata/lineage standards, partner with product and engineering teams, and produce reusable modeling artifacts to enable analytics and AI/ML use cases.

Leads complex enterprise AI programs from inception through production deployment. Coordinates data science, machine learning, data engineering, product, architecture, and client teams while overseeing RAG pipelines, multi-agent AI ecosystems, and knowledge graphs. Manages risks, dependencies, technical challenges, stakeholder communication, delivery progress, and strategic outcomes across globally distributed teams.

Designs and prototypes scalable agentic AI architectures across Azure, AWS, or GCP. Responsibilities include multi-agent orchestration, LLM applications, RAG pipelines, memory and vector search, enterprise integrations, cloud-native engineering, code reviews, AI governance, security guardrails, and stakeholder leadership. The role requires hands-on development, framework evaluation, and translating business needs into production-ready AI platforms.