Spear AI builds AI and data systems for national security, with project work centered on maritime domain awareness and unmanned sensor systems. Its stack pairs AWS GovCloud and Azure Government with ACAS and Nessus, and job posts repeatedly cite CMMC compliance and air-gapped deployment. Senior-weighted, engineering-heavy hiring and a shift away from C++ and Protocol Buffers toward Rust point to a hardware-to-cloud modernization push.
Spear AI is a privately held company founded in 2020 and headquartered in Washington, DC, with 51–200 employees. It applies machine learning, including acoustic ML and reinforcement learning, to problems faced by the U.S. national security sector. Its work spans cloud architecture, data platforms and unmanned maritime sensor hardware, supported by a stack that includes Python, TypeScript, Kubernetes, Dagster, Apache Iceberg and Kafka. The company hires in the United States.
Spear AI uses AWS, AWS GovCloud, Azure Government, Kubernetes, Terraform, Pulumi, GitLab CI/CD, Python, TypeScript, Rust, PostgreSQL, Apache Iceberg, Kafka and Dagster, plus ACAS and Nessus for security scanning.
Job posts point to a next-generation data and AI platform for maritime domain awareness, unmanned maritime sensor systems, CI/CD and DevSecOps pipelines, and Model Context Protocol server integration.
Yes. Engineering dominates Spear AI's hiring, which skews toward senior roles, with smaller openings in security, data, design and sales, all based in the United States.
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Spear AI'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.
