Principal DevOps Engineer

Company Description Reva.AI is a unified access control and AI security platform designed for modern agentic and cloud-native environments. As organizations adopt AI agents, LLM-powered applications, and distributed cloud services, Reva.AI enables security and product teams to implement dynamic, intent-aware access controls and enforce least privilege across human, machine, and AI identities. The platform combines AI workload discovery, behavioral analytics, policy governance, and runtime enforcement to provide a robust trust layer for AI-driven systems at scale. Guided by a mission to secure the AI era with context-aware, continuously enforced policies, Reva.AI aims to redefine enterprise security with a unified authorization control plane for applications, infrastructure, data, and AI systems. Role Description The Principal DevOps Engineer is a full-time, on-site role based in Bengaluru South, responsible for leading the design, implementation, and maintenance of scalable, secure, and highly available infrastructure for Reva.AI’s platform. This role involves architecting CI/CD pipelines, optimizing build and deployment processes, and automating infrastructure provisioning and configuration using modern DevOps and cloud-native practices. The Principal DevOps Engineer will collaborate closely with engineering, security, and product teams to ensure reliable releases, implement observability and monitoring, and uphold best practices for performance, reliability, and compliance. Day-to-day responsibilities include troubleshooting complex production issues, mentoring other engineers, improving operational efficiency, and driving the adoption of new tools and processes that support secure AI and access control workloads. Qualifications Strong experience with DevOps practices, including CI/CD pipeline design, build automation, and release management. Deep expertise in cloud platforms (such as AWS, GCP, or Azure) and cloud-native technologies (containers, orchestration, infrastructure as code). Proficiency in scripting and automation languages (such as Python, Bash, or similar) to streamline operations and deployments. Solid understanding of security, identity, and access control principles, especially in AI-driven or distributed systems environments. Hands-on experience with monitoring, logging, and observability tools to maintain system health and performance. Proven ability to design and operate high-availability, scalable, and resilient systems in production. Experience mentoring and guiding engineering teams, with strong collaboration and communication skills. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Background in enterprise security, AI platforms, or authorization systems is highly beneficial.