Job Location : Arlington, VA (Onsite/Hybrid from Day 1)

Job 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.

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.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

The base compensation range for this role in the posted location is: 90786- 120673

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.