DevOps Manager

About Us:

Zenity is the leader in AI Agent Security and the first company to bring an agent-centric security platform to market. As enterprises accelerate AI agent adoption, we are establishing the security framework for how AI agents are secured and governed at enterprise scale.

We deliver full-lifecycle visibility, governance, detection, prevention, and response for AI agents from build time to runtime, across SaaS, home-grown platforms, and end-user devices. Backed by $180M+ in total funding, including a $125M Series C led by Norwest, with participation from SoftBank Vision Fund 2 and Microsoft's M12, Zenity is trusted by Fortune 500 and Global 2000 enterprises worldwide.

Join us in shaping how AI agents are secured at enterprise scale.

We are looking for a highly skilled and passionate DevOps Manager to lead the team responsible for our critical infrastructure, platform services, and core cross-product capabilities, ensuring scalability, reliability, maintainability, and high performance.

This role is ideal for an experienced engineering leader who is passionate about technology, thrives in high-growth environments, enjoys solving complex technical challenges, and is eager to drive technological innovation.

Requirements:

• 2+ years of experience managing engineering teams.

• 10+ years of professional experience in the software industry.

• Strong hands-on experience with modern programming languages such as Python, TypeScript, or Go.

• Strong understanding of software engineering principles, including SOLID, infrastructure architecture, Infrastructure as Code, and GitOps.

• Experience designing and operating large-scale cloud services on AWS, Azure, or GCP.

• Strong proficiency in DevOps practices, observability, and operating production cloud-based systems.

• Hands-on experience working in Agile environments and building CI/CD pipelines.

• Experience in high-growth startup environments, with a strong mindset around scalability, automation, and engineering efficiency.

• Familiarity with large-scale data technologies such as Kafka, Spark, and OpenSearch.