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 environment 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 explicit 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 - Devops (Gurugram)
🏢 SiriusAI
📍 Gurugram