Staff Site Reliability Engineer

About RateGain RateGain Travel Technologies Limited is a global provider of AI-powered SaaS solutions for travel and hospitality, working with 13,000+ customers and 700+ partners across 160+ countries. RateGain helps travel and hospitality businesses accelerate revenue generation through acquisition, retention, and wallet share expansion. Today, RateGain is one of the world's largest processors of electronic transactions, price points, and travel intent data, enabling revenue management, distribution, and marketing teams across hotels, airlines, destination marketing organizations, metasearch companies, package providers, car rentals, travel management companies, cruises, and ferries to drive better business outcomes. Founded in 2004 and headquartered in India, RateGain works with 33 of the Top 40 Hotel Chains, 4 of the Top 5 Airlines, 7 of the Top 10 Car Rental companies, and leading Destination Marketing Organizations, Online Travel Agents, and metasearch platforms, including 25 Global Fortune 500 companies, unlocking new revenue every day. Recognized globally for its innovation and impact, RateGain has been named Best Digital Marketing Agency by HotelTechReport Awards and Best Channel Manager by the World Travel Tech Awards. The company has also been certified as a Great Place to Work® in the USA, Spain, and India, with recognition in India for seven consecutive years. In 2025, RateGain was honored as Emerging Company of the Year at The Economic Times Awards for Corporate Excellence, named among Deloitte India Technology Fast 50 for the sixth time, and won Excellence in Best AI Solution Showcase for UNO VIVA at the CII National AI Awards 2025, among other industry recognitions. The Mission To strengthen RateGain's Site Reliability Engineering and DevOps capabilities by building and maintaining secure, reliable, and scalable cloud infrastructure. The role will focus on improving infrastructure automation, CI/CD processes, Kubernetes operations, monitoring, and production reliability while driving platform engineering initiatives and adopting AI-driven operational practices. Key Responsibilities Cloud Infrastructure & Automation Design, build, and maintain scalable cloud infrastructure on Google Cloud Platform (GCP). Implement and manage Infrastructure as Code (IaC) using Terraform to automate infrastructure provisioning and management. Optimize cloud infrastructure for performance, availability, security, and cost efficiency. Troubleshoot complex infrastructure and application runtime issues to ensure business continuity. Kubernetes & Container Management Deploy, manage, secure, and monitor containerized applications running on Kubernetes. Build and maintain Kubernetes clusters, ensuring high availability, scalability, and reliability. Develop and maintain Kubernetes Custom Resource Definitions (CRDs) and operators to automate complex infrastructure workflows. Work closely with engineering teams to identify the right deployment architecture, including serverless and container-based solutions. DevOps & CI/CD Engineering Design, implement, and improve CI/CD pipelines to enable faster and more reliable application deployments. Automate build, testing, deployment, and infrastructure management processes. Work with tools such as Jenkins, ArgoCD, Codefresh, and other DevOps technologies. Collaborate with software engineering teams to improve deployment efficiency and development workflows. Site Reliability & Production Operations Establish and improve SRE best practices to ensure application availability, reliability, and performance. Implement monitoring, logging, alerting, and incident management processes. Troubleshoot production issues, perform root cause analysis, and implement preventive measures. Improve system resilience, disaster recovery readiness, and operational efficiency. Platform Engineering & AIOps Drive platform engineering initiatives to simplify infrastructure management and improve developer productivity. Develop reusable infrastructure components and automation frameworks. Leverage AIOps tools and techniques to improve incident detection, automate responses, and enable proactive monitoring. Explore and implement AI-driven tools to improve engineering efficiency and operational reliability. Functional KPIs Maintain high application and infrastructure availability against agreed service-level objectives (SLOs). Reduce Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR) production incidents. Improve CI/CD pipeline efficiency and reduce application deployment time. Increase infrastructure automation and reduce manual operational activities. Improve Kubernetes cluster performance, security, and resource utilization. Optimize GCP infrastructure costs through effective resource management and automation. Reduce recurring production incidents through root cause analysis and preventive measures. Strategic KPIs Strengthen the overall SRE culture and establish standardized reliability practices across engineering teams. Drive adoption of Infrastructure as Code and automated cloud infrastructure management. Build a scalable and secure cloud platform to support business growth and application demands. Improve developer productivity through platform engineering and self-service infrastructure capabilities. Advance AIOps adoption to enable proactive monitoring, intelligent alerting, and automated incident response. Improve infrastructure security, compliance, and operational resilience. Drive continuous improvement in engineering efficiency, cloud optimization, and production reliability. Key Competencies Google Cloud Platform: Strong hands-on experience in designing, managing, and troubleshooting GCP infrastructure. Infrastructure as Code: Expertise in Terraform and infrastructure automation. Kubernetes & Containers: Advanced knowledge of Kubernetes, Docker, container security, monitoring, and troubleshooting. Platform Engineering: Experience building scalable internal platforms, Kubernetes CRDs, and custom operators. CI/CD & DevOps: Strong understanding of deployment automation and tools such as Jenkins, ArgoCD, and Codefresh. Programming & Scripting: Proficiency in Python, Shell scripting, or Go for infrastructure automation and troubleshooting. Site Reliability Engineering: Strong understanding of monitoring, incident management, system reliability, and performance optimization. AIOps & AI Adoption: Knowledge of AI-driven monitoring, automated incident response, and modern AI development tools. Linux & System Fundamentals: Strong understanding of Linux operating systems, networking, and computer science fundamentals. Problem-Solving & Collaboration: Ability to troubleshoot complex technical challenges, work independently, and collaborate effectively with engineering teams. Education & Work Experience Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical field. 8+ years of experience in Site Reliability Engineering, DevOps, Cloud Engineering, or related infrastructure engineering roles. Extensive hands-on experience with Google Cloud Platform (GCP), Terraform, Kubernetes, and containerized applications. Proven experience in managing production infrastructure, troubleshooting application issues, and improving system reliability. Strong experience in infrastructure automation, CI/CD pipelines, monitoring, and cloud security. Experience in platform engineering, developing Kubernetes CRDs and operators, and implementing AIOps solutions. Hands-on experience with Python, Shell scripting, or Go. Experience working in fast-paced, cloud-native, and AI-driven engineering environments. Cloud, Kubernetes, or CNCF certifications will be an added advantage. Experience with SOC2 compliance, distributed systems, and tools such as Datadog, Jenkins, ArgoCD, and Codefresh is preferred. Familiarity with AI development tools such as Cursor, ChatGPT, Gemini, and Claude is desirable. Strong ownership, problem-solving ability, collaboration, adaptability, and a continuous improvement mindset. Equal Opportunity Employer We are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.