Sai Kishore Chintakindhi
Data Architect | AI-Driven Compliance | American Express | GCP | Big Data
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cloud data architect and compliance automation engineer with over a decade of experience in large-scale data systems. He currently leads AI-driven data governance initiatives at American Express, architecting pipelines that combine codified contracts, real-time validation, and regulatory alignment. His published research focuses on AI-powered data lineage, scalable metadata-driven frameworks, and CI/CD enforcement in financial systems.
Area of Expertise
Codified Data Contracts & LLM-Powered Compliance in CI/CD Workflows
In regulated industries, data quality, compliance, and governance must be enforced continuously—not just audited periodically. This session introduces a practical framework to codify data contracts and embed compliance rules directly into CI/CD pipelines using large language models (LLMs). It will explore how enterprise data teams can shift compliance left by integrating AI to detect schema drift, policy violations, and lineage gaps in real time.
Real-world examples from financial services will illustrate how LLM-driven metadata enforcement and automated validation workflows reduce audit risk and ensure data integrity at scale. The session also highlights scalable implementation strategies using GCP BigQuery, Spark, and Airflow, with a focus on cost-effective governance.
Building Trustworthy Generative AI Systems: From Prompt to Production
As generative AI moves from experimentation to enterprise deployment, ensuring trust, reproducibility, and safety becomes critical. This session explores how to design production-grade generative AI pipelines—from prompt engineering and output validation to bias mitigation and observability.
Attendees will learn how to integrate human-in-the-loop (HITL) workflows, metadata versioning, and feedback loops for improving generation quality. Real examples will showcase how enterprise teams in finance and customer service are using LLMs like GPT and open-source models to automate tasks, while enforcing ethical and business guardrails.
We’ll also discuss how to architect scalable, audit-ready GenAI workflows using Vertex AI, LangChain, and prompt versioning systems.
Sai Kishore Chintakindhi
Data Architect | AI-Driven Compliance | American Express | GCP | Big Data
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