Senior AI Governance Architect

Northrop Grumman

Falls Church (VA)

Remote

USD 129,000 - 194,000

Full time

14 days+

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Benefits offered by this job

Health insurance

Life and disability insurance

Savings plan

Paid holidays

Paid time off

Job summary

Northrop Grumman seeks a Senior Principal AI Governance Engineer to design and operationalize governance across AI capabilities and platforms, translating policies into technical controls and automated workflows.

Based in Falls Church, VA with possible remote arrangements, the role collaborates with Privacy, Legal, Cybersecurity and Enterprise Architecture to ensure safe, compliant AI systems throughout the lifecycle.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field with 8 years of relevant experience or a Master's degree with 6 years of relevant experience.
Experience designing, building, or integrating AI/ML systems or data-driven applications in an enterprise environment.
Experience with data security, privacy, cybersecurity, or related control environments.
Demonstrated experience translating governance, risk, or compliance requirements into technical controls, automated workflows, or monitoring/observability solutions.
Hands‑on experience implementing technical guardrails or standards for complex systems (e.g., service‑level policies, access control, audit logging, monitoring, or approvals).
Experience working with cross‑functional stakeholders, such as Privacy, Legal, Cybersecurity, Compliance, or Enterprise Architecture.
Strong analytical, problem‑solving, and communication skills with the ability to explain complex technical and governance concepts to both technical and non‑technical audiences.

Responsibilities

Design and implement technical capabilities that support the AI Governance Framework throughout the AI lifecycle, from intake and registration through monitoring and observability.
Translate AI policies, standards, and requirements into technical controls and automated governance workflows.
Develop mechanisms and tooling to identify, register, classify, and assess AI use cases, and drive a common taxonomy for evaluation across the enterprise.
Establish governance patterns for AI capabilities and develop reusable governance components that can be embedded into AI development and deployment pipelines.
Automate and define standards for evidence collection and documentation to support governance, audit, and assurance needs.
Design and implement technical guardrails and best practices for AI systems, including usage constraints, access patterns, and safeguards.
Partner with Privacy, Legal, Cybersecurity, Global Supply Chain, and other governance bodies to integrate existing enterprise controls into AI systems and workflows.
Develop or scale capabilities that provide enterprise visibility into AI systems and their lifecycle, including the detection and management of Shadow AI.
Implement mechanisms for ongoing monitoring and observability of AI systems rather than relying solely on point-in-time assessments.
Contribute to the continuous improvement of AI governance practices, patterns, and tooling across the organization.