Defense analytics and RF signal processing for the Intelligence Community
Boeing Intelligence & Analytics builds software and systems for U.S. intelligence agencies, with deep focus on RF signal processing, analytics pipelines, and hardware-software integration. The stack reflects a mature defense contractor: C++, Python, Java running on AWS with Kubernetes orchestration, paired with specialized tooling (FPGA, DoDAF, IBM DOORS, SysML) for classified environments. Engineering dominates hiring (30 of 36 roles), with mid-to-senior seniority split, signaling active scaling of core development teams rather than rapid headcount growth.
Notable leadership hires: Chief Architect
Boeing Intelligence & Analytics, founded in 2016 and headquartered in Annapolis Junction, Maryland, is a subsidiary of Boeing Defense, Space and Security serving the U.S. Intelligence Community. The organization spans 201–500 employees focused on advanced analytics, RF signal processing, systems integration, and embedded/FPGA development. Active projects center on integrating legacy and new software stacks, RF application testing, system migrations, disaster recovery, and security hardening. The company faces recurring operational challenges around backup/recovery planning, network bottlenecks, security compliance, and data volume management in resource-constrained environments.
C++, Python, Java, PostgreSQL, AWS (including Direct Connect, VPC, CloudFormation), Kubernetes, Docker, Terraform, Ansible, Elastic Stack (Prometheus, Grafana, CloudWatch), plus defense-specific tools: DoDAF, IBM DOORS, SysML, and FPGA development frameworks.
RF signal processing applications, hardware-software integration, system migrations and upgrades, disaster recovery strategies, analytics and visualization tools, system performance monitoring automation, and security measures implementation for intelligence mission programs.
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Boeing Intelligence & Analytics'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.