Combat systems and weapons integration for U.S. Navy platforms
In-Depth Engineering builds combat system software and integration services for U.S. Department of Defense platforms—primarily AEGIS ship systems and missile defense. The stack is heavily weighted toward embedded C++, systems modeling (SysML, MBSE), and CAD/simulation tools (MATLAB, ANSYS, SolidWorks), with DevSecOps infrastructure (GitLab, Kubernetes, Docker) layered on top. Current hiring is concentrated in engineering roles at mid and senior levels, aligned with active projects in ship modernization and ballistic missile defense—suggesting capacity expansion rather than headcount replacement.
In-Depth Engineering is a veteran-owned small business defense contractor headquartered in Fairfax, Virginia, with facilities across Maryland, Rhode Island, New Jersey, and California. The company develops combat system software and provides systems integration, test, and waterfront support services to the U.S. Navy and wider Department of Defense. Work includes design, development, and integration for platforms such as AEGIS destroyers, submarine combat systems (AN/SQQ-89, AN/BQQ-10), and ground-based missile defense systems. Beyond in-house development, the company operates offshore engineering teams delivering on-site modernization support and IT services. The organization spans 201–500 employees and operates under strict defense security compliance regimes.
Primary languages: C++, Python, Java, Perl. Build/collab: GitLab, Bitbucket, Jira, Confluence. Systems modeling: SysML, MBSE, IBM DOORS. CAD/simulation: SolidWorks, Creo, NX, ANSYS, ABAQUS. Infrastructure: Red Hat Enterprise Linux, Kubernetes, Docker, Nexus.
Active projects include AEGIS ship integration and combat system displays, ground-based missile defense systems, ballistic missile threat detection, ship modernization efforts, and continuous security monitoring and vulnerability assessment for defense IT systems.
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In-Depth Engineering Corporation's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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