Cyberhaven - Principal Software Engineer (AI Security)
Requirements
• You have a strong track record building backends that are actively used at scale, and you've contributed significantly to and extended their architecture, not just shipped features. • You have deep, hands-on experience developing large applications in Go. • You've operated databases at very large scale. Knowledge of GCP services (BigTable, BigQuery, Spanner) is a plus. • You have experience profiling and optimizing distributed code that uses large databases and streaming platforms. • Experience building connectors that integrate at the API level with SaaS applications commonly used in the enterprise is a plus, especially with AI/LLM platforms. • You have hands-on production experience with microservices and Kubernetes. • You have excellent verbal and written communication skills in English, and can be available to frequently communicate with distributed teams in Europe and the US. • You thrive in fast-paced environments tackling ambiguous challenges, and you enjoy shipping with velocity. • You have a customer-centric mindset and enjoy direct feedback from customers. • You are based in India or the EU. • AI Tools Disclosure: As part of Cyberhaven's hiring process, we use recruiting tools that include AI-powered features to help with tasks like scheduling, note-taking, workflow automation, and other recruiting activities ("AI Tools"). The AI Tools may process information you provide during the application and interview process. When AI-assisted interview note taking is used, candidates are notified in advance and have the option to opt out of the AI-assisted interview note taking. • AI Tools Disclosure:
Responsibilities
• Architect, extend, and optimize a large-scale, highly scalable, fault-tolerant system that handles large graph datasets at enterprise scale processing billions of AI-related events from hundreds of thousands of endpoints in real time, with sub-second latency requirements. • Set technical direction for how Cyberhaven secures data flowing into and out of AI models, GenAI applications, and agents, shaping architecture decisions that will define this product line for years to come. • Architect and implement security features that protect customer data end-to-end. • Solve real-world scaling problems that require thorough performance analysis and troubleshooting. • Work with a modern, constantly evolving microservices based stack including Go, Kubernetes, BigTable, BigQuery, Spanner, Redis, Docker, and Etcd. • Design and build connectors that integrate at the API level with SaaS and AI platforms commonly used in the enterprise (e.g. ChatGPT, Copilot, and other GenAI tools). • Write secure-by-design, hardened software that withstands real-world attacks while processing untrusted data and communicating with hundreds of thousands of endpoints over the internet. • Raise the technical bar across the team through architecture reviews, mentorship of senior/staff engineers, and setting patterns others follow.
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