Lead Full Stack Engineer - AI/ML Systems
Reston, VA, United States • Posted June 06, 2026
Job Type:
Full-time
Location:
Reston, VA
Posted:
June 06, 2026
Category:
other-general
Application Deadline:
June 11, 2026
Role Description
Responsibilities
Noblis is seeking a **_Lead Full Stack Engineer_** to design, develop, and deploy full-stack applications that integrate advanced AI/ML capabilities for mission-critical law enforcement and intelligence operations. You'll architect enterprise-scale systems across multi-enclave environments (unclassified through sensitive compartmented), building both rapid prototypes and hardened production applications that directly support operational requirements.
This is a **hands-on technical leadership role** where you'll spend 60% of your time coding and 40% architecting, mentoring, and driving technical strategy across a cross-functional team.
**Job Responsibilities**
+ Architecture & Design
+ Design full-stack web applications for multi-enclave (unclassified and sensitive) on-prem, cloud, and hybrid environments
+ Architect complex data pipelines and ETL processes spanning large, heterogeneous, and sensitive data types
+ D...
Noblis is seeking a **_Lead Full Stack Engineer_** to design, develop, and deploy full-stack applications that integrate advanced AI/ML capabilities for mission-critical law enforcement and intelligence operations. You'll architect enterprise-scale systems across multi-enclave environments (unclassified through sensitive compartmented), building both rapid prototypes and hardened production applications that directly support operational requirements.
This is a **hands-on technical leadership role** where you'll spend 60% of your time coding and 40% architecting, mentoring, and driving technical strategy across a cross-functional team.
**Job Responsibilities**
+ Architecture & Design
+ Design full-stack web applications for multi-enclave (unclassified and sensitive) on-prem, cloud, and hybrid environments
+ Architect complex data pipelines and ETL processes spanning large, heterogeneous, and sensitive data types
+ D...
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