Cyberhaven
Staff/Principal Software Engineer (AI Security)
Principal backend engineer building scalable systems to secure AI data flows in real time, using Go, Kubernetes, and GCP services.
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Remote
- Seniority
- Principal
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- 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.
Full description
About the role
Cyberhaven is redefining data security by tracing how sensitive data actually moves across endpoints, cloud, SaaS, and now AI tools and agents. Our AI Security team builds the backend systems that give enterprises real-time visibility and control over how their data flows into and out of LLMs, GenAI applications, and autonomous agents. We're looking for a Staff/Principal Backend Software Engineer to be one of the most senior technical voices on this team: an early contributor with substantial influence over the architecture of a new and rapidly evolving product line, solving multiple exciting technical challenges along the way.
What you'll do
- 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.
Who you are
- 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.