AI Data Management Specialist

SAIC•Bethesda, MD

About The Position

SAIC® is a premier Fortune 500® mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, civilian and intelligence markets includes secure high-end solutions in mission IT, enterprise IT, engineering services and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives. We are approximately 24,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.5 billion. For more information, visit saic.com . For ongoing news, please visit our newsroom . SAIC is seeking an experienced and skilled AI Data Management Specialist to support the Chief AI Officer and Chief Data Officer (CAIO/CDO) at one of our Intelligence customers. The ideal candidate will have a solid foundation in data management, including practical and strategic expertise across the data lifecycle, data protection, and stakeholder coordination. In this role, you will engage with technical and non-technical senior government data managers to develop, implement, and refine their data management strategies while ensuring alignment with best practices in data protection, privacy, and civil liberties. Familiarity with AI concepts and vectorization as it relates to AI is required, and knowledge of zero trust principles, and data architecture is highly desirable to enhance your contributions to this critical mission.

Requirements

Active TS/SCI with Poly is required
Bachelor’s degree with 8+ years of relevant experience, Associate’s degree with 10+ years of relevant experience, or Master’s degree with 6+ years of relevant experience.
Solid background in data management, with a firm, practical, and strategic understanding of the data lifecycle and its application in government or enterprise environments.
Understanding of vectorization in AI and its relationship to data usage and analytics.
Strong expertise in data protection, especially regarding issues such as data spills, safeguarding personal information, and addressing civil liberties.
Ability to coordinate with senior technical and non-technical stakeholders, including government senior data managers, to align data management initiatives with organizational priorities.
Familiarity with AI concepts and their implications for data usage and management.

Nice To Haves

Knowledge or experience with zero trust architecture principles.
Expertise in data architecture design, principles, and governance, with the ability to speak confidently about its implications for strategy and implementation.
Experience working for or with Intelligence Community (IC) stakeholders or other government agencies.
Strong communication and interpersonal skills to convey complex technical concepts to diverse audiences.

Responsibilities

Data Lifecycle Management: Provide expertise in practical and strategic aspects of the data lifecycle, including data collection, storage, usage, sharing, and archival/disposal.
Guide senior government stakeholders in the development and execution of comprehensive data management plans aligned with mission goals and compliance requirements.
Data Protection and Governance: Deliver practical and strategic guidance on data protection, addressing risks related to data spills, personal information security, and civil liberties.
Ensure compliance with data protection policies, laws, and standards, and promote best practices to safeguard sensitive information and preserve privacy.
Stakeholder Coordination: Act as a critical liaison, working directly with senior government data managers and technical teams to bridge technical and non-technical perspectives.
Facilitate communication and understanding of data management priorities, challenges, and solutions.
AI and Emerging Technologies: Apply a foundational understanding of AI to advise on data strategies that enable AI implementation and clear adoption paths.
Contribute to discussions and planning related to advanced concepts such as vectorization in AI and data-driven solutions.
Strategic Recommendations: Support senior leadership by identifying and addressing gaps in data infrastructure, strategy, and implementation.
Advise on policies and practices related to zero trust architecture, data architecture, and cross-organizational data-sharing initiatives.