Intelligence-community data, analytics and program evaluation services
Orbis is a McLean-based contractor serving US intelligence and defense clients with data engineering, OSINT and analytic services. Current hiring is research-heavy and senior-skewed, centered on program evaluation and strategic communications assessments for an intelligence community client, not pure software builds. The stack pairs Kafka, Apache NiFi and Elasticsearch with multi-cloud AWS, GCP and Azure plus Terraform, pointing to data-flow pipelines built for federated government environments.
Orbis is a privately held firm founded in 2008 and headquartered in McLean, Virginia, with 51–200 employees. It provides intelligence and security services to public and private sector clients, with a strong focus on the US intelligence community. Its capability areas include digital and open source intelligence, secure data architecture, zero trust, data mesh and federation, C2 interoperability, and AI-assisted analyst tooling. The company also delivers research, program evaluation and web and data applications for federal intelligence programs. Hiring is concentrated in the United States.
Orbis uses Python, Pandas, Kafka, Apache NiFi, Elasticsearch, Kibana and Grafana, runs on AWS, GCP and Azure, and manages infrastructure with Docker, Kubernetes, Terraform, Jenkins and GitLab. Tableau and Power BI handle BI.
Yes. Research is the largest hiring area at Orbis, with mostly senior roles focused on qualitative research, survey design and program evaluation for a US intelligence community client. Hiring is accelerating.
Orbis is running program evaluations and strategic communications assessments for a US intelligence community client, building web and data applications for federal intelligence programs, and implementing a new AP system.
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Orbis'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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