Job Description
Senior Cloud Data & AI Architect
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
Salary Range- $150,000-$175,000 a year