Backend Software Engineer, Censys

• 3+ years of software engineering experience building distributed systems (i.e. data ingestion pipelines, databases, services)
• Experience with object-oriented programming - we use Go
• Experience with at least one cloud provider, like: AWS, Azure, or GCP
• Experience or familiarity with message queue technologies, like: AWS Kinesis , Google Pub/Sub, Kafka, or other
• Experience working with databases, like: BigTable, Cloud Spanner, HBase, Cassandra, or other
• Understanding of core distributed systems concepts such as scalability, fault tolerance, and reliability
• Familiarity with using AI
• Ability to write understandable, testable code with an eye towards maintainability
• Strong communication skills and the ability to work effectively with other engineers and product managers

Desirable

• We’re looking to hire a Software Engineer (Backend, Distributed Systems) to build scalable services, APIs, frameworks, and internal tooling that process large amounts of data and make them highly available, providing direct value to customers and other parts of our organization
• Censys operates distributed infrastructure for Internet-wide scanning, and you will help us continue our mission to build high-quality datasets, APIs, and engineering foundations that turn research and detection ideas into production-ready capabilities
• At Censys, we believe in working iteratively while keeping the big picture in mind. We’re expanding our data platform to enable future products and features that make the Internet more explainable by adding richer context and showing complex relationships. We’re looking for someone who is curious, collaborative, and excited to grow while contributing to our mission
• Help build large scale, real-time services and applications which leverage our massive datasets to power internal APIs and external applications
• Build tooling, libraries, frameworks, and services that support security, research and data platform initiatives
• Productionize prototypes into reliable internal tools, services, or platform capabilities
• Participate in planning and technical discussions with engineering and product teams to help build the right solutions
• Develop and maintain systems such as data pipelines, messaging systems, databases, caching layers, and services that run in the cloud or on-prem
• Work with Machine Learning Engineers and Security Researchers to realize solutions that affect security outcomes