Agentic AI Architect / Lead - Snowflake Cortex
About The Position
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. We are seeking a highly experienced Agentic AI Architect / Lead with deep hands-on expertise in Snowflake Cortex, AI Agents, Generative AI, RAG architectures, and enterprise AI solutions. This role will be responsible for designing, evaluating, optimizing, and scaling Agentic AI platforms while providing technical leadership to a team of engineers, architects, and AI practitioners. The ideal candidate will have proven experience building AI agents using Snowflake Cortex capabilities, implementing enterprise-grade GenAI solutions, and driving AI adoption through best practices, governance, and architecture standards. The candidate should be capable of quickly assessing existing AI agents, identifying improvement opportunities, and delivering scalable Agentic AI frameworks aligned with business objectives.
Requirements
- 8+ years of experience in Data Engineering, AI/ML, Data Architecture, or Enterprise Technology Solutions.
- 5+ years of hands-on experience building and deploying Generative AI and Agentic AI solutions.
- Strong practical experience with Snowflake Cortex including: Cortex Search, Cortex Analyst, Vector Embeddings, Semantic Search, RAG Architectures.
- Proven experience designing and implementing AI Agents and Agentic AI frameworks in enterprise environments.
- Deep understanding of: Autonomous Agents, Agent Orchestration, Prompt Engineering.
- Experience building conversational AI, AI copilots, intelligent assistants, and workflow automation solutions.
- Strong understanding of vector databases, embeddings, semantic search, and knowledge retrieval architectures.
- Hands-on experience with Python, SQL, Snowpark, and API integrations.
Nice To Haves
- Experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar Agentic AI frameworks.
- Experience building AI copilots, autonomous business workflows, and enterprise AI platforms.
- SnowPro Certifications (Core, Advanced, or Architect).
- Experience with Azure OpenAI, OpenAI, Anthropic Claude, Gemini, or other LLM ecosystems.
- Experience with AWS, Azure, or GCP cloud platforms.
- Knowledge of MLOps, LLMOps, AI observability, and governance frameworks.
- Experience leading enterprise AI transformation initiatives.
- Understanding of modern data stack technologies such as dbt, Airflow, Kafka, Spark, Fivetran, or Matillion.
Responsibilities
- Lead the architecture, design, and implementation of enterprise-scale Agentic AI solutions using Snowflake Cortex.
- Evaluate existing AI agents and autonomous workflows, identify performance gaps, and recommend improvements for scalability, reliability, and business value.
- Design and implement multi-agent architectures, orchestration frameworks, and intelligent automation workflows.
- Architect AI-powered applications leveraging Snowflake Cortex capabilities, including: Cortex Search, Cortex Analyst, Cortex LLM Functions, Document AI, Vector Embeddings, Semantic Search, RAG (Retrieval-Augmented Generation).
- Establish best practices for prompt engineering, agent memory, tool usage, context management, reasoning, and AI governance.
- Lead technical decision-making for Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar platforms.
- Design semantic layers and vector-based retrieval solutions to support enterprise AI applications.
- Mentor and guide engineering teams on AI agent design patterns, evaluation methodologies, and deployment strategies.
- Define AI agent monitoring, performance metrics, evaluation frameworks, and governance standards.
Benefits
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
