Sr. Principal AI Systems Engineer Security Clearance

Position: Sr. Principal AI Systems Engineer with Security Clearance
RELOCATION ASSISTANCE:
No relocation assistance available CLEARANCE TYPE:
None TRAVEL:
Yes, 10% of the Time 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 level AI Systems Engineer to join the AI Infrastructure Engineering team within the Insights & Intelligence (i2) organization. This role will report to the Manager of AI Infrastructure Engineering and will be remote and/or hybrid supporting the Falls Church, VA office. Insights & Intelligence (i2) is reimagining decision making at Northrop Grumman. As part of our Chief Information & Digital Office (CIDO), i2 works with all enterprise domains and businesses to drive our data, analytics & AI transformation.

The selected candidate will work with a team of Dev Ops and AI Systems Engineers focused on data ingestion, AI infrastructure, and AI model deployment at scale ensuring AI solutions are both economical and trustworthy. Collaboration will be necessary with functional teams, product owners, and i2 leadership to evaluate use case feasibility and shape the roadmap for new and existing AI systems.

Responsibilities include but are not limited to the following:
* Architect and implement end-to-end pipelines for data ingestion, model training, validation, and serving.

* Develop self-service APIs and CLI tools that allow internal teams to submit data for vectorization and manage index resources without recurring engineering support.

* Build internal SDKs, CLI tools, and libraries that simplify model deployment, monitoring, and lifecycle management for cross-functional teams

* Research emerging embedding models and vector-search technologies and determine applicability to overall AI strategy

* Stay current on emerging AI hardware and software frameworks; prototype and assess new technologies for adoption.

* Conduct cost-benefit analyses of alternative cloud providers, on-prem hardware, and managed AI services.

* Implement AI use cases ensuring compliance with relevant regulations and security standards, implementing necessary controls

* Work alongside data scientists, software engineers, and i2 functional teams to contribute to the roadmap for new and existing AI systems.

Basic Qualifications:

* Must have a Bachelor's degree in Computer Science, Software Engineering, Information Systems or a related field

* Must have 8 years of relevant experience with a Bachelors degree OR 6 Years of relevant experience with a Masters degree OR 4 Years of relevant experience with PhD

* Must have at least 3 years of experience focused on AI or MLOps

* Must have a minimum of 2 years working with cloud (AWS or Azure) infrastructure and services with the ability to work in hybrid-cloud or on-prem environments

* Must have experience with relevant programming languages (e.g., Python, Java, Powershell/Bash) and AI/ML frameworks

* Must have basic knowledge of database technologies (e.g., SQL, No

SQL) and distributed computing systems

* Must have experience with evaluating and implementing cybersecurity for AI systems

* Must have demonstratable knowledge of matching hardware configuration to AI system requirements

* Must have exceptional verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholder's

Preferred Qualifications:

* Experience with cloud (AWS or Azure) native AI Services (Sage Maker, EKS, ML, AKS, etc.)

* Prior experience with load testing…