Join to apply for the Databricks Architect role at SAIC
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Join to apply for the Databricks Architect role at SAIC
Minimum Clearance Required None
Job ID 2508687
Location REMOTE WORK, DC, US Date Posted 2025-08-18 Category Engineering and Sciences Subcategory Solutions Archt Schedule Full-time Shift Day Job Travel No Minimum Clearance Required None Clearance Level Must Be Able to Obtain Public Trust Potential for Remote Work Yes Description We are seeking an experienced and versatile Databricks Architect to lead the architectural design and implementation of Databricks-based solutions within a broader AI/ML platform environment. This role is part of the core platform team enabling scalable, secure, and reusable data science and GenAI workflows across federal mission use cases. The ideal candidate will have strong data architecture skills, a deep understanding of the AI/ML lifecycle, and familiarity with both traditional and emerging GenAI technologies. This architect plays a vital role in enabling the full lifecycle of AI/ML model development for IRS data scientistsfrom data ingestion and feature engineering to model training, deployment, and monitoring. As the platform team serves data science users directly, the architect must ensure Databricks capabilities are accessible, extensible, and aligned with user workflows. You will collaborate with infrastructure, security, compliance, and AI engineering teams to ensure Databricks capabilities are integrated seamlessly with supporting services such as S3, Amazon SageMaker, Bedrock, and shared pipeline frameworks. You will also work closely with the Product Manager and Chief Architect to inform roadmap evolution and ensure technical feasibility, performance, and alignment with broader architectural direction. As a hands-on architect, you will guide the design of workspaces, cluster policies, CI/CD integration, and governance structures that enable secure and efficient AI/ML model development and deployment. Key ResponsibilitiesReferrals increase your chances of interviewing at SAIC by 2x
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