About Sirius AI Sirius AI is a US-headquartered AI consulting services and products company with operations in India. We work with financial services enterprises to deliver data-driven solutions across multiple geographies. Our teams build AI, data-platform, and cloud-native solutions focused on measurable business outcomes. Role Overview We are looking for a hands-on DevOps Engineer with 4–5 years of experience to help build, automate, secure, and operate reliable cloud infrastructure and delivery pipelines. The role will work closely with engineering, AI/ML, data, security, and product teams to support development and production environments across AWS and Azure.

Key Responsibilities
Cloud Infrastructure & Automation
• Provision, configure, and maintain cloud infrastructure across AWS and Azure.
• Implement and maintain Infrastructure as Code using Terraform; exposure to CloudFormation, Bicep, or ARM templates is beneficial.
• Support workplace setup and configuration across development, staging, and production.
• Assist with cloud cost monitoring, resource optimization, backup practices, and operational hygiene. CI/CD & Release Engineering
• Build, maintain, and troubleshoot CI/CD pipelines using Jenkins, GitHub Actions, Azure DevOps, or AWS CodePipeline.
• Automate build, test, deployment, and rollback workflows; support safe release practices across environments.
• Work with Git-based version control and artifact repositories such as JFrog Artifactory, Nexus, or Azure Artifacts. Containers & Kubernetes
• Build and maintain container images using Docker and deploy containerized applications.
• Support Kubernetes workloads on Amazon EKS and/or Azure AKS, including deployments, services, ingress, configuration, and troubleshooting.




• Use Helm for packaging and deployment; exposure to Argo CD or Flux CD and GitOps practices is an advantage. Monitoring, Reliability & Incident Support
• Configure and maintain monitoring, alerting, dashboards, and logs using Prometheus, Grafana, CloudWatch, Azure Monitor, or Log Analytics.
• Investigate application and infrastructure incidents, perform initial root-cause analysis, and document corrective and preventive actions.
• Support service reliability through health checks, capacity monitoring, backup validation, and operational runbooks. DevSecOps & Access Management
• Integrate security and quality checks into delivery pipelines using tools such as SonarQube, Trivy, Checkov, AWS Inspector, or Microsoft Defender for Cloud.
• Manage application secrets using AWS Secrets Manager, Azure Key Vault, or HashiCorp Vault.
• Follow least-privilege access, secure configuration, patching, and change-management practices; support compliance requirements where applicable. Scripting & AI/ML Platform Support
• Write scripts and automation using Python, Bash, Shell, or PowerShell to reduce manual operational work.
• Support infrastructure and deployment needs for AI/ML workloads, including model-serving environments and GPU workloads when required.
• Collaborate with AI/ML and engineering teams to improve deployment repeatability, observability, and operational readiness. Required Qualifications




• 4–5 years of hands-on experience in DevOps, cloud engineering, platform engineering, or a related role.
• Practical experience with AWS and/or Azure cloud services; willingness to work across both platforms.
• Hands-on experience with CI/CD pipelines and Infrastructure as Code, preferably Jenkins or GitHub Actions/Azure DevOps and Terraform.
• Working knowledge of Docker and Kubernetes; experience with EKS or AKS is preferred.
• Experience with monitoring, logging, troubleshooting, and supporting production or production-like environments.
• Comfortable scripting in Python, Bash, Shell, or PowerShell.
• Understanding of cloud networking, IAM/RBAC, secrets management, and basic security best practices.
• Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience. Preferred Skills
• Exposure to AI/ML or MLOps tools such as MLflow, Kubeflow, Amazon SageMaker, Azure Machine Learning, or OpenSearch.
• Experience with GitOps tools such as Argo CD or Flux CD.
• Exposure to policy-as-code tools such as OPA or Sentinel.
• Experience in fintech, BFSI, or other regulated environments.
• Relevant certifications such as AWS, Azure, CKA/CKAD, or Terraform Associate. What Success Looks Like
• Reliable, repeatable infrastructure provisioning and application deployments.
• Faster and safer releases through automation and clear rollback procedures.
• Improved visibility into platform health through useful alerts, dashboards, and logs.
• Timely incident support, clear documentation, and actionable follow-up improvements.
• Effective collaboration with engineering and AI/ML teams.

📌 Senior Consultant (Gurugram)
🏢 SiriusAI
📍 Gurugram