AI/ML and data systems for federal defense and cybersecurity missions
Nyla Technology Solutions builds data infrastructure and AI/ML systems for U.S. federal government agencies, with deep specialization in malware analysis, mission-critical analytics, and cloud-native modernization. The stack reveals an organization balancing legacy system integration (ServiceNow, GCCS-J modernization) with modern data platforms (PostgreSQL, MongoDB, Apache NiFi, Kibana, Grafana), while actively adopting infrastructure-as-code tooling (Ansible, Nomad, SALT) — a pattern consistent with DoD compliance and accreditation constraints. Heavy hiring in engineering and security (37 of 46 roles) reflects the operational intensity of federal cybersecurity work.
Nyla Technology Solutions is a privately held software and systems engineering firm based in Columbia, Maryland, serving U.S. federal government agencies since 2013. The company specializes in AI/ML, data science, cybersecurity, and cloud computing, with particular depth in malware analysis, analytics pipelines, and next-generation mission capabilities. Core technical efforts center on modernizing legacy command-and-control systems (GCCS-J), building scalable cloud databases, and operationalizing complex cyber data analysis at enterprise scale. The organization operates across 51–200 employees with engineering, security, and data teams handling accreditation-ready, mission-critical systems.
Nyla uses PostgreSQL, MongoDB, Python, Java, Kubernetes, OpenShift, Apache NiFi, Power BI, GitLab CI/CD, Docker, AWS, and observability tools (Grafana, Kibana). Currently adopting Ansible, Nomad, and Nutanix.
Projects include malware analysis modernization, GCCS-J backend microservices, custom analytics pipelines, ServiceNow automation, cloud database scaling, and accreditation/modernization efforts for federal mission systems.
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Nyla Technology Solutions'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 →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.