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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Snowflake Architect - Cortex & Agentic AI Lead - **Company:** Capgemini - **Location:** Irving, TX, United States - **Experience:** Expert - **Salary:** $90,786.0 - $120,673.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, ARM Architecture, Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Sharing, Data Warehousing, Machine Learning, Role-Based Access Control, Search Technologies, SQL Databases, Data Streaming, Enterprise Search, Enterprise Data Management, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Apache Spark, Generative AI, Data Layers, Data Lakes, AI Platforms, Apache Kafka, Virtual Agents, Automation Anywhere - **Published:** July 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=15bdf85c50fddfee ## About the Role The ideal candidate will combine strong Snowflake architecture experience with practical expertise in Cortex AI capabilities, RAG architectures, AI agents, semantic search, and enterprise AI solution delivery., * 10+ years of experience in Data Architecture, Data Engineering, Analytics, or Enterprise Data Platforms. * Strong expertise in Snowflake architecture, including Warehouses, Snowpark, Streams, Tasks, Data Sharing, Time Travel, Zero-Copy Cloning, Resource Monitors, and Security Frameworks. * Deep hands-on experience with Snowflake Cortex, including: * + Cortex Search + Cortex Analyst + Cortex LLM Functions + Vector Embeddings + Semantic Search + RAG (Retrieval-Augmented Generation) Architectures + Document AI * Proven experience designing, evaluating, and improving Agentic AI solutions and AI agent frameworks. * Strong understanding of AI agent orchestration, autonomous workflows, prompt engineering, semantic retrieval, and enterprise GenAI architectures. * Expertise in SQL, data modeling, ETL/ELT design, and cloud-based data platforms. * Experience designing scalable solutions for analytics, reporting, AI, and machine learning workloads. * Strong knowledge of data governance, data quality, lineage, security, and compliance frameworks., * Experience building and optimizing enterprise AI agents and Agentic AI applications. * Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI orchestration frameworks. * SnowPro Core, Advanced, or Architect Certifications. * Experience with dbt, Airflow, Kafka, Spark, Fivetran, Matillion, or similar modern data stack technologies. * Knowledge of vector databases, enterprise search, semantic models, and knowledge retrieval frameworks. * Experience working with AWS, Azure, or GCP ecosystems. * Experience in large-scale enterprise environments and AI transformation initiatives. ## Description We are seeking a highly experienced Snowflake Architect with deep expertise in Snowflake Cortex and Agentic AI to lead and guide a team of approximately 25 engineers and AI practitioners in delivering enterprise-scale Agentic AI solutions. This role requires a hands-on architect who can quickly assess existing AI agents, identify strengths and gaps, recommend improvements, and establish best practices to accelerate successful AI adoption across the organization., * Lead end-to-end architecture and solution design for Snowflake-based data, analytics, and AI platforms. * Provide technical leadership and mentorship to a team of 25+ engineers, architects, and developers delivering Agentic AI solutions. * Assess existing AI agents and Agentic AI implementations, identifying what is working well, what is not, and providing recommendations for optimization and scalability. * Establish architectural standards, governance frameworks, and best practices for building, deploying, and managing AI agents. * Architect and implement AI-powered solutions leveraging Snowflake Cortex capabilities, including Cortex Search, Cortex Analyst, LLM Functions, Document AI, vector embeddings, semantic search, and RAG patterns. * Drive the adoption of Agentic AI frameworks and guide teams on designing autonomous, intelligent, and business-aligned AI workflows. * Design and optimize Snowflake data warehouses, data lakes, and lakehouse architectures for analytics, reporting, AI, and machine learning workloads. * Design ingestion frameworks including batch, streaming, Snowpipe, and real-time processing solutions. * Develop AI-ready data foundations, semantic layers, and reusable data products that support advanced analytics and Generative AI use cases. * Collaborate with Data Engineers, Data Scientists, Product Owners, Business Stakeholders, and AI teams to align technical solutions with business objectives. * Define performance metrics, evaluation criteria, and governance processes for AI agents and enterprise AI solutions. * Implement secure and scalable architectures with strong focus on RBAC, data governance, data privacy, masking policies, encryption, and compliance requirements. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Got AI ideas but no money? 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