About this role
A candidate who enjoys tackling complex backend challenges at scale and is motivated by building robust security solutions for emerging AI applications would find this role suitable. This position involves contributing to the development and evolution of Cyberhaven’s AI Security platform, which focuses on protecting data across the lifecycle of LLMs, GenAI applications, and AI agents. The engineer will be responsible for designing and optimizing highly scalable, fault-tolerant backend systems capable of processing billions of events in real time with strict latency requirements. A key focus will be developing security capabilities to safeguard sensitive customer data as it interacts with AI tools and services.
This role exists to address the need for advanced data security solutions for the agentic enterprise, moving beyond traditional protection methods. The engineer will directly influence the architecture of the AI Security platform and solve complex distributed systems problems related to performance and reliability. It is ideal for someone who values building secure-by-design software and thrives in an environment where they can shape the future of data protection for AI workflows.
Successful candidates will possess a strong background in building production systems using Go and experience managing microservices in a distributed environment. They will collaborate closely with various teams across different geographic locations to deliver a reliable and performant security platform.
What you will do
- Design, extend, and optimize large-scale, fault-tolerant backend systems that process billions of events in real time, ensuring sub-second latency.
- Build security features to protect sensitive customer data flowing into and out of LLMs, GenAI applications, and AI agents.
- Contribute to the overall architecture and evolution of Cyberhaven’s AI Security platform.
- Resolve real-world scaling and distributed systems issues through performance analysis, profiling, optimization, and troubleshooting.
- Develop and deploy production backend services utilizing Go (Golang).
- Create API-level integrations and connectors for enterprise SaaS platforms, including GenAI and LLM-based applications.
- Write secure-by-design, hardened software capable of withstanding attacks while handling untrusted data.
- Collaborate with engineering, product, and distributed teams across India, Europe, and the US.
What you need
- Possess over four years of software engineering experience, demonstrating a strong history of building backend systems that operate at scale.
- Must have strong, hands-on experience with Go (Golang) and a proven track record of shipping production backend services in Go.
- Experience building and operating distributed systems, microservices, and applications managed by Kubernetes in a production setting is required.
- Demonstrated experience working with databases at significant scale is necessary.
- Experience profiling, troubleshooting, and optimizing distributed applications involving large databases or streaming platforms is beneficial.
- Experience building API-level integrations or connectors with enterprise SaaS applications is a plus.
- Familiarity with AI/LLM platforms is particularly relevant to this role.
- A strong understanding of reliability, performance, and security when handling large volumes of sensitive or untrusted data is essential.
Nice to have
- Experience with GCP services such as BigTable, BigQuery, or Spanner
- Experience building API-level integrations or connectors with enterprise SaaS applications
- Experience with AI/LLM platforms
Benefits
- Committed to creating a diverse environment
- Equal opportunity employer
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
The posting indicates that the team collaborates closely with engineers across India, Europe, and the US.
What is the compensation structure?
The posting does not specify the salary for this role.
What is the primary technology stack?
The required stack includes Go (Golang), Kubernetes, BigTable, BigQuery, Spanner, Redis, Docker, and Etcd.
What is the team structure like?
The role involves close collaboration with engineers, product teams, and distributed teams across India, Europe, and the US.