Senior Principal AI Governance Engineer 

RELOCATION ASSISTANCE: No relocation assistance available

CLEARANCE REQUIRED FOR START: No

CLEARANCE TYPE: Secret

TRAVEL: No
## Description

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.

Northrop Grumman is seeking a  Senior Principal AI Engineer  to join the Data & AI Governance & Strategy organization. This role will help design and operationalize the technology capabilities required to govern AI across the enterprise.

Role Overview

The Senior Principal AI Governance Engineer will sit at the intersection of AI development, data security, privacy, risk, compliance, and enterprise architecture. In this role, you will translate AI governance requirements into scalable technical controls, automation, and observability that can be embedded across AI capabilities and platforms.

You will report to the Manager, Data & AI Governance & Strategy and collaborate closely with Privacy, Legal, Cybersecurity, Global Supply Chain, and other governance bodies to ensure AI systems are designed, deployed, and operated in a safe, compliant, and responsible manner.

The primary location for this position is Falls Church, VA; alternative work locations/arrangements will be considered, including 100% virtual/remote, in accordance with business needs and management appro val.

Responsibilities include, but are not limited to:

- 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.

Basic Qualifications

- Must have a 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.

Preferred Qualifications

- Experience designing, implementing, or operationalizing an enterprise AI Governance Framework across the full lifecycle (intake, registration, classification, risk assessment, monitoring, observability).
- Experience developing reusable governance components (e.g., templates, SDKs, APIs, pipelines, policies-as-code) that can be embedded into AI development and deployment workflows.
- Experience establishing common taxonomies and classification schemes for AI or data use cases, including risk categorization and tiering.
- Experience implementing ongoing monitoring and observability for AI systems, including detection and management of Shadow AI and unapproved tools.
- Experience with enterprise governance, risk, and compliance platforms, specifically: Credo
- OneTrust

- Experience with AI and data platforms and tooling such as Databricks and IBM WatsonX (or similar enterprise AI platforms).
- Experience with international AI governance, including: Emerging AI regulations (e.g., elements aligned with the EU AI Act or other international frameworks)
- Operating AI governance in multi-jurisdiction, global environments

- Familiarity with AI safety, model risk management, or Responsible AI practices (e.g., fairness, transparency, accountability, robustness).
- Experience in large, complex, and/or highly regulated industries (e.g., defense, aerospace, financial services, healthcare).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern data/ML engineering practices (e.g., MLOps, DevSecOps, infrastructure-as-code).

Primary Level Salary Range: $129,300.00 - $193,900.00

The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions.

Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business.

The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.

Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit http://www.northropgrumman.com/EEO. U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.