Principal AI Engineer Software
$137.8k - $206.8kNorthrop Grumman
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. Description
At Northrop Grumman, we 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.
Northrop Grumman is seeking a Principal AI Software Engineer to support the development, integration, and deployment of advanced AI-enabled software solutions to support our Systems Engineering Integration & Test (SEIT) department. As a member of the SEIT department you’ll work in a fast-paced team environment alongside physicists, design engineers, and superconducting foundry engineers to make our technologies a reality. This position will serve on-site at Spectrum Center, San Diego .
Responsibilities:
· Design, develop, integrate, and sustain AI-enabled software products and supporting systems across cloud and local/on-premises environments.
· Translate mission, customer, and business needs into secure, scalable, and maintainable technical solutions.
· Identify system, workflow, or architecture gaps and independently develop improvements that increase performance, reliability, security, or efficiency.
· Secure and harden full-stack solutions, including infrastructure, platforms, applications, data flows, and development pipelines.
· Evaluate, adapt, and securely leverage open-source technologies to accelerate delivery while maintaining engineering rigor and security standards.
· Experience developing or integrating AI/ML-enabled applications into operational or production environments.
· Experience securing end-to-end systems spanning infrastructure, applications, data, interfaces, and deployment pipelines.
· Working knowledge across adjacent domains such as cyber security, networking, DevOps, systems engineering, or platform engineering.
· Experience evaluating and incorporating open-source frameworks, models, or tooling in a secure and supportable manner.
· Familiarity with modern software delivery practices including CI/CD, containerization, automation, and infrastructure/platform operations.
· Demonstrated ability to influence technical direction, present to senior leadership, and work effectively across organizations.
· Experience mentoring engineers and supporting team technical development.
· Track record of delivering measurable business or mission value through cost savings, productivity improvements, force multiplication, or new capability delivery.
· Work across software, cyber, networking, DevOps, and systems engineering disciplines to implement end-to-end solutions.
· Perform technical trade studies, solution analysis, and architectural assessments to support sound engineering decisions.
· Communicate technical approaches, risks, status, and results to leadership, stakeholders, and cross-organizational teams.
· Incorporate emerging research, tools, and engineering practices into practical solutions where they provide measurable value.
· Mentor other engineers, contribute to technical growth across the team, and help drive execution toward program and business objectives.
Basic Qualifications for Principal AI Software Engineer:
- Bachelor’s degree in Computer Science, Software Engineering or related STEM discipline with 5 years of relevant experience; or 3 years with a Master’s degree; or 1 year with a PhD.
- Current DoD 8570 IAT Level II Certification (Security+) or higher.
- Candidate must be a US Citizen.
- Experience translating technical concepts and program information to others.
- Clearance: A current/active DoD Secret clearance.
- Experience developing or deploying AI/ML-enabled applications for practical or operational use cases.
- Experience leading technical efforts across multiple engineering disciplines and guiding teams through implementation.
- Experience identifying when AI is not the right solution and proposing a better engineering alternative.
Preferred Qualifications for Principal AI Software Engineer:
- Experience developing or integrating AI/ML-enabled applications into operational or production environments.
- Experience securing end-to-end systems spanning infrastructure, applications, data, interfaces, and deployment pipelines.
- Experience assessing AI/ML approaches against data quality, data volume, compute limitations, security requirements, and deployment constraints.
- Working knowledge across adjacent domains such as cyber security, networking, DevOps, systems engineering, or platform engineering.
- Experience evaluating and incorporating open-source frameworks, models, or tooling in a secure and supportable manner.
- Familiarity with modern software delivery practices including CI/CD, containerization, automation, and infrastructure/platform operations.
- Demonstrated ability to influence technical direction, present to senior leadership, and work effectively across organizations.
- Experience mentoring engineers and supporting team technical development.
- Experience with GPU optimization, distributed inference, or deployment in constrained compute environments.
- Integration of AI into larger end-to-end systems.
- Experience integrating AI into secure or regulated environments.
- Track record of delivering measurable business or mission value through cost savings, productivity improvements, force multiplication, or new capability delivery.
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