Senior Cloud Data & AI Architect

Locations: Los Angeles, CA / Dallas, TX / Chicago, IL Must Have Technical/Functional Skills • Architect enterprise data platforms for data lake, Lakehouse, streaming systems. • Design data integration and data pipeline patterns • Should be able to evaluate new technologies and run proof of concepts. • Should be able to set data and AI strategy for data organization. • Established data Quality, lineage and metadata standards • Ensured compliance with privacy, security and regulation • Drives adoption of responsible AI frameworks • Created architectural guardrails • Drive consensus on standards (eg data contracts, lineage) across different data organizations • Reviews design and elevate architectural thinking across teams • Creates reusable patterns, templates and reference architectures • Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation • Design and implement AI and Gen AI solution for data value chain • Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI). • Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning. • Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate). • Experience with A2A orchestration, agent memory strategies, and tool calling. • Strong grasp of enterprise architecture, data governance, and security protocols. • Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines. • Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation • Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage. • Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models. • Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate). Roles & Responsibilities • Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients. • Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure Design and implement AI and Gen AI solution for data value chain • Design data integration pipelines (batch, real-time, big data) and analytics platforms • Define and implement data governance, quality, meta data, and lineage frameworks and should be able to leverage GenAI capabilities. • Act as a trusted advisor to senior business and IT stakeholders Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI). • Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models. • Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows. • Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage. Generic Managerial Skills, If any • 15–20 years of experience in data architecture, data engineering, and analytics platforms • Strong consulting experience in large BFSI transformation programs • Hands-on expertise with Snowflake and Databricks (Lakehouse architecture) • Design and implement AI and Gen AI solution for data value chain • Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation • Experience with cloud data services in aws,azure,gcp • Strong background in data integration, reporting, and big data ecosystems • Experience working in regulated environments with data governance and compliance requirements • Excellent stakeholder communication and leadership skills Show more Show less