Solution Architect — Data & AI Platform
TypeContract
LocationWorldwide
Posted3 hours ago
🚀 We're Hiring: Solution Architect — Data & AI Platform
📍 Remote
💼 Contract
🧰 Experience: 10+ yrs
🛠️ Skills: CI/CD, SQL
We are seeking a Principal Solution Architect — Data & AI Platform to lead the design and enablement of AI-ready data capabilities on a modern Databricks Lakehouse foundation. This role will focus on building the architecture patterns required to support LLM-powered analytics, conversational AI, agentic AI workflows, governed data products, semantic layers, metadata intelligence, RAG.
Roles & Responsibilities:
Define and drive the Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns.
Architect secure LLM and GenAI enablement patterns, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation.
Design agentic AI capabilities to support data platform operations such as metadata discovery, catalog enrichment, lineage analysis, data quality investigation, documentation generation, pipeline troubleshooting, test generation, and operational runbook support.
Establish architecture standards for AI-ready data products, certified metrics, semantic layers, business definitions
Originally posted on Himalayas
📍 Remote
💼 Contract
🧰 Experience: 10+ yrs
🛠️ Skills: CI/CD, SQL
We are seeking a Principal Solution Architect — Data & AI Platform to lead the design and enablement of AI-ready data capabilities on a modern Databricks Lakehouse foundation. This role will focus on building the architecture patterns required to support LLM-powered analytics, conversational AI, agentic AI workflows, governed data products, semantic layers, metadata intelligence, RAG.
Roles & Responsibilities:
Define and drive the Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns.
Architect secure LLM and GenAI enablement patterns, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation.
Design agentic AI capabilities to support data platform operations such as metadata discovery, catalog enrichment, lineage analysis, data quality investigation, documentation generation, pipeline troubleshooting, test generation, and operational runbook support.
Establish architecture standards for AI-ready data products, certified metrics, semantic layers, business definitions
Originally posted on Himalayas
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