Software Architect

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. About the Role: Zenity is looking for a Software Architect to lead the technical evolution of our next-generation AI cybersecurity platform. You'll work across teams to solve the company's most challenging architectural problems while remaining deeply hands-on - building prototypes, validating new technologies, and helping engineering teams deliver production-ready solutions. The role requires both deep engineering expertise and the ability to shape the architecture of large-scale data, cloud, and AI systems that power our platform.

Requirements: Requirements: • 7+ years in a senior technical leadership role (Principal Architect, Staff Engineer, Lead Engineer, or equivalent), with a strong track record designing and delivering large-scale distributed systems and cloud-native architectures in production. • Strong background in cybersecurity and secure system design, including cloud security principles and enterprise compliance frameworks; experience in SaaS or cybersecurity products is a significant advantage. • Deep, hands-on experience with AWS, GCP, or Azure, and strong expertise in Kubernetes and containerized environments, with the ability to design for scale while maintaining simplicity and cost awareness. • Strong background in modern data platforms, streaming architectures, and complex event processing for large-scale, real-time workloads. • Hands-on experience integrating GenAI capabilities into production systems - RAG pipelines, agentic workflows, or LLM-based integrations - and familiarity with AI-native engineering practices, including coding agents. • Experience designing multi-tenant SaaS platforms with strong isolation and scalability, and excellent communication skills to influence architecture across engineering, product, and data science.