Responsibilities

- Infrastructure design & management: Architect and manage our cloud infrastructure (likely on AWS/Azure/GCP) to support Rhias applications and data pipelines. Set up and maintain scalable server architectures (compute clusters, container orchestration with Kubernetes or similar, serverless components where appropriate) to handle our travel platform’s growing load.

- Design, implement, manage, and scale new and existing cloud infrastructure

- Leverage Infrastructure as Code (IaC) tools like Terraform to manage cloud resources

- Manage Cloud cost and review & optimize on a monthly basis

- Respond to and remediate issues and incidents as part of an on-call rotation

- CI/CD pipeline ownership: Develop and maintain continuous integration and continuous deployment pipelines that enable frequent, reliable releases of current features. Automate build, test, and deployment processes, ensuring that code can move from development to production with minimal friction and maximum quality.

- Monitoring & alerting: Implement comprehensive monitoring, logging, and alerting solutions (using tools like Prometheus, Grafana, ELK/EFK stack, or cloud-native monitoring services). Keep a close eye on system performance, uptime, and anomalies. Set up alerts and incident response processes to address issues proactively – for example, detecting traffic spikes in booking transactions or anomalies flagged by AI monitoring and responding before they impact users.

- Security & compliance: Work closely with the security best practices to harden our infrastructure. Manage secrets, certificates, and ensure secure configurations of servers and services. Implement access controls and auditing, and stay vigilant about protecting user data and maintaining compliance with relevant standards (especially important in handling personal travel information).

- Automation & tooling: Write scripts and use Infrastructure-as-Code (IaC) tools (like Terraform, CloudFormation, or Ansible) to automate provisioning and configuration of environments. Strive for a “cattle, not pets” approach to servers – enabling quick, reproducible deployments and recoveries. Use AI tools or smart automation where possible (for example, automated scaling policies based on predictive algorithms, or AI ops tools that help analyze log patterns).

- Collaboration with development teams: Work hand-in-hand with software engineers, QA, and data scientists to ensure that the infrastructure meets their needs. Advise on deployment strategies,



optimize environment configurations for new features (like ensuring a new AI microservice has the right resources), and assist developers in debugging environment-specific issues.

- Performance & cost optimization: Regularly review system performance (response times, throughput) and identify bottlenecks. Optimize our use of cloud resources for both performance and cost-effectiveness – for example, using CDN for content delivery, right-sizing instances, or leveraging spot instances where applicable. Ensure our platform can handle peak loads (like seasonal travel surges) gracefully.

Requirements

- Experience: 5+ years of experience in DevOps, Site Reliability Engineering, or system administration with a focus on automation. Proven experience managing cloud infrastructure for a SaaS application is essential. Startup experience is a plus, indicating you can handle fast-paced and evolving requirements.

- Cloud & containers: Strong expertise with at least one major cloud provider (AWS, GCP, or Azure). Hands-on experience with containerization and orchestration – you should be comfortable deploying and managing Docker containers, and orchestrating them with Kubernetes or similar systems in production.

- CI/CD & automation: In-depth knowledge of CI/CD tools (Jenkins, GitLab CI, CircleCI, etc.) and version control systems (Git). Ability to design pipelines that include automated testing and deployment. Significant experience with scripting (Bash, Python, or PowerShell) and using Infrastructure as Code (Terraform, CloudFormation, or Ansible/Puppet/Chef) to automate environment setup.

- Monitoring & troubleshooting: Proficiency in setting up monitoring/alerting (CloudWatch, Datadog, New Relic, etc.) and diagnosing complex system issues. A knack for performance tuning at various layers – application, database, network.

Experience with log management and analysis.

- Security mindset: Solid understanding of network and application security in a cloud environment. Familiar with implementing security best practices (VPC configuration, IAM roles, security groups, encryption of data at rest/in transit). Knowledge of compliance regimes relevant to SaaS (like SOC2, GDPR) is a bonus.

- Domain relevance:



Experience with SaaS products and comfort in the travel/technology sector is essential. This includes understanding the uptime and responsiveness expectations of users globally. Any experience in systems handling travel data or transaction flows (e.g., booking systems) will be beneficial.

- AI/ML pipelines (nice to have): While not mandatory, exposure to deploying or maintaining infrastructure for AI/ML models (such as model serving frameworks, GPU instances, or big data processing like Spark) is a plus given our AI-centric approach.

- Soft skills: Excellent problem-solving skills and the ability to work under pressure during incidents. Good communication skills to document processes and train developers on DevOps practices. A collaborative attitude – eager to work with team members across the org to achieve common goals.

Preferred Qualifications

- Education: Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent work experience). Relevant certifications (AWS Certified DevOps Engineer, Certified Kubernetes Administrator, etc.) are a plus and demonstrate a strong foundational knowledge.

- Tooling & stack: Familiarity with our specific tech stack is beneficial. For instance, if our application is built on Node.js, Python, etc., knowledge of deploying and optimizing those environments.

Experience with database administration (for databases we use, e.g., MySQL, PostgreSQL, MongoDB) and caching systems (Redis, CDN configuration) would be helpful.

- DevSecOps & testing: Experience implementing DevSecOps practices such as automated security scanning (SAST/DAST in the CI pipeline) and infrastructure testing. Knowledge of chaos engineering or resilience testing tools to ensure system robustness.

- Scaling experience: Direct experience scaling a system from a small user base to a significantly larger one. Stories of how you tackled specific growth challenges (e.g., refactoring a monolith to microservices, optimizing build times, managing cost explosion) will set you apart.

- Contribution & community: Active participation in DevOps communities or open-source projects. Maybe you’ve contributed to a popular DevOps tool or maintain your own. This shows passion and expertise.

- Cultural fit: A passion for travel or personal experience using travel apps extensively can give you empathy for the product we’re building. Additionally, having worked in a global team or supporting systems with international users prepares you for Rhia’s worldwide reach.

📌 Senior Devops Engineer (Gurugram)
🏢 Rhia AI
📍 Gurugram