AI security platform protecting generative and agentic models from supply chain to runtime
HiddenLayer operates an integrated security platform for AI applications, spanning supply chain vulnerability scanning, runtime defense, posture management, and automated red teaming. The stack reveals deep ML infrastructure (TensorFlow, PyTorch, Keras) paired with production-grade orchestration (Kubernetes, Terraform, ArgoCD), indicating engineering that bridges threat modeling and deployment at scale. The hiring mix — sales-forward (4 roles) with sparse engineering (1 open) — signals a scaling sales organization evangelizing a newer security category, while internal challenges around deployment velocity and cloud AI integrations suggest the platform is still maturing its multi-cloud operational footprint.
Notable leadership hires: Enterprise Account Director
HiddenLayer develops security tooling for organizations deploying generative and agentic AI systems. Founded in 2022, the company addresses a range of attack surfaces: prompt injection, model theft, supply chain compromise, adversarial manipulation, and data poisoning. The product unifies multiple security functions (supply chain scanning, runtime defense, compliance posture, penetration testing) into a single platform. Customers span private and public sector organizations adopting AI with compliance or risk constraints. The company is based in Austin, TX and operates with a 51–200-person team.
HiddenLayer uses Python, Go, TypeScript, and React for application development; TensorFlow, PyTorch, and Keras for ML model analysis; Kubernetes, Terraform, Docker, and ArgoCD for cloud infrastructure; and AWS, Azure, and GCP for cloud platforms. The company also integrates with Salesforce, NetSuite, and Stripe for business operations.
HiddenLayer is headquartered in Austin, TX and is currently hiring exclusively within the United States.
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HiddenLayer'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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