PLATH Systems & Integration builds SIGINT and electronic warfare systems in Hamburg, and its job posts point to a modernization of how those systems are built and run. The stack pairs C++, LabVIEW and SysML with Kubernetes, Argo CD, Terraform/OpenTofu and PyTorch. Active projects cover containerized SIGINT architecture, cloud platform evaluation for signal data and air-gapped IT environments. Hiring is engineering-heavy, with a steady pace across Germany and Switzerland.
Notable leadership hires: Head Participation Controlling, Technical Lead
PLATH Systems & Integration is an independent systems integrator based in Hamburg, Germany, focused on reconnaissance and electronic warfare. It develops and deploys systems that detect and analyze HF and V/UHF signals. Its product range spans mobile, naval and airborne platforms. The company reports more than 350 systems delivered and in operation worldwide. It belongs to a family-owned group, was founded in 1954 and employs 201–500 people.
PLATH uses C++, Python, Java, Kotlin and LabVIEW, with Kubernetes, Helm, Argo CD, Terraform/OpenTofu and Ansible for infrastructure. Its stack also includes PyTorch, Keras and DVC for ML, plus PostgreSQL and Elasticsearch.
Current projects include containerized SIGINT system architecture, evaluating cloud platforms for SIGINT data processing, signal processing algorithms, a Kubernetes and DevOps platform, and structuring air-gapped IT environments.
PLATH is hiring in Germany and Switzerland at a steady pace. Engineering makes up most of its open roles, with additional openings in sales, operations and finance.
Other companies in the same industry, closest in size
PLATH Systems & Integration'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.