Jobs at Censys

Build and lead large-scale frontend projects for enterprise account management, integrations, settings, and Censys Platform experiences. Partner with Design and Product, make architectural decisions, and deliver accessible, performant, maintainable interfaces. Establish strong standards for unit, integration, and end-to-end testing, component architecture, accessibility, state management, data fetching, and frontend performance. Collaborate with backend engineers and contribute to shared component libraries, data visualizations, and complex grid interfaces.

Lead Censys’ product management organization and unified exposure management strategy across attack surface management and supply chain intelligence. Define product vision, roadmap, and customer workflows; partner with engineering, design, AI, research, and go-to-market teams; establish scalable product processes; identify new platform opportunities; represent the company externally; and drive measurable adoption, usage, and revenue outcomes while hiring and developing product talent.

Build and deploy AI-powered features for internet-scale threat intelligence workflows. Develop and fine-tune LLMs, RAG pipelines, vector search, and AI-driven analytics to summarize findings and automate investigations. Create secure, context-aware user experiences while evaluating model performance with RAGAS, LangSmith, and regression testing. Collaborate with product, frontend, data engineering, and other teams to deliver low-latency, reliable AI capabilities.

Build and maintain highly available, scalable distributed systems and real-time data services supporting Internet intelligence products. Responsibilities include developing data pipelines, messaging systems, databases, caching layers, APIs, tooling, libraries, and cloud or on-premises services; productionizing prototypes; improving reliability and maintainability; and collaborating with engineering, product, machine learning, and security research teams.

Build highly available, scalable distributed systems and real-time data services supporting Internet-wide scanning, DNS resolution, certificate ingestion, security research, and customer applications. Responsibilities include developing data pipelines, messaging systems, databases, caching layers, tooling, frameworks, and cloud or on-premises services; productionizing prototypes; and collaborating with engineering, product, machine learning, and security teams. The role emphasizes maintainable, testable code, reliability, monitoring, and long-term platform development.

Build highly available, scalable distributed systems and real-time services supporting Internet-wide scanning, DNS resolution, certificate ingestion, data pipelines, messaging, databases, caching, and APIs. Productionize prototypes, develop reusable tooling and platform capabilities, maintain cloud and on-premise systems, and collaborate with engineering, product, machine learning, and security teams.

Build and deploy applied machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets. Develop feature pipelines, training datasets, evaluation frameworks, confidence scoring, and production inference services. Collaborate with engineering, research, security, and product teams to transform raw Internet telemetry into high-quality datasets and customer-facing insights.

Build highly available, scalable distributed systems and real-time services supporting Internet-wide scanning, data ingestion, APIs, security research, and machine learning initiatives. Responsibilities include developing data pipelines, messaging systems, databases, caching layers, tooling, and cloud or on-premises services; productionizing prototypes; collaborating with engineering, product, machine learning, and security teams; and maintaining reliable, observable systems.

Build and deploy AI/LLM-powered features and RAG pipelines for internet-scale threat intelligence. Prototype, fine-tune, evaluate, and optimize models; integrate AI into platform services; implement CI/CD, regression testing, and security guardrails; collaborate across product, frontend, and data teams to deliver real-time, low-latency AI-driven analytics and automation.

The Staff Backend Engineer will lead the Exposure Management team, oversee backend services migration, enhance system design, and mentor engineers, focusing on reducing attack surface exposures.

Leads the Data Collection engineering team responsible for Internet scanning, distributed systems, data pipelines, and operational tooling. Owns people development, technical roadmap, delivery, architecture, reliability, observability, incident management, and cost efficiency. Partners with Product, Research, Security, Infrastructure, and engineering stakeholders to translate priorities into production capabilities and measurable improvements in coverage, freshness, accuracy, scalability, and reliability.