Cloud Data & AI Architects (1147335)

Location: Minneapolis, MN

Pay

$170,000.00 USD Annually - $175,000.00 USD Annually

About the role

Architect enterprise data platforms for data lake, Lakehouse, and streaming systems. Design data integration and data pipeline patterns, evaluate new technologies, and run proof-of-concept initiatives. Set data and AI strategy for the data organization, establish data quality, lineage, and metadata standards, and ensure compliance with privacy, security, and regulatory requirements. Drive adoption of responsible AI frameworks and create architectural guardrails. Foster consensus on standards (e.g., data contracts, lineage) across data organizations, review designs, and elevate architectural thinking across teams. Develop reusable patterns, templates, and reference architectures.

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 solutions for the data value chain.
• Design data integration pipelines (batch, real-time, big data) and analytics platforms.
• Define and implement data governance, quality, metadata, and lineage frameworks, leveraging 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.

Requirements

• 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).
• Very strong understanding and experience with Data products, data mesh, and Medallion Architecture implementation.
• Experience with cloud data services in AWS, Azure, and 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.
• 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 MLOps pipelines.