DevOps Engineer

Role Overview

Location: Noida
Scope: Supporting Klypup markets across India, Singapore, and the UAE

We are seeking a skilled and motivated DevOps Engineer to bridge the gap between software development, cloud infrastructure, and IT operations by designing, automating, and maintaining secure, scalable, reliable, and cost-efficient technology platforms.

The successful candidate will be responsible for implementing modern CI/CD practices, Infrastructure as Code (IaC), container orchestration, observability, cloud security, and operational automation across cloud and hybrid environments.

The role will collaborate closely with software developers, AI/ML engineers, cloud architects, security teams, and customers to accelerate software delivery while maintaining operational excellence.

Core Responsibilities

1. Continuous Integration & Continuous Delivery (CI/CD)

• Design, implement, and maintain automated CI/CD pipelines for application development, testing, security validation, and deployment.
• Manage deployment workflows using GitHub Actions, GitLab CI/CD, Jenkins, AWS CodePipeline, or Azure DevOps.
• Implement automated testing, deployment approvals, rollback mechanisms, and release strategies such as blue-green and canary deployments.
• Improve software delivery efficiency through standardized and reusable pipeline templates.

2. Infrastructure as Code (IaC) & Cloud Automation

• Provision, configure, and manage cloud and hybrid infrastructure using Terraform, AWS CloudFormation, Ansible, or Pulumi.
• Develop reusable infrastructure modules and automation scripts.
• Implement infrastructure version control, configuration management, and automated environment provisioning.
• Support cloud infrastructure across AWS, Azure, or GCP, with AWS experience preferred.

3. Containerization & Kubernetes Orchestration

• Build, deploy, secure, and manage containerized applications using Docker and Kubernetes.
• Support managed container platforms such as Amazon EKS, Azure AKS, or Google GKE.
• Implement Helm-based deployments, container registries, autoscaling, and workload management.
• Troubleshoot container performance, networking, availability, and deployment issues.

4. Observability, Reliability & Incident Management

• Implement centralized monitoring, logging, tracing, and alerting using Amazon CloudWatch, Prometheus, Grafana, OpenTelemetry, or equivalent technologies.
• Monitor infrastructure health, application performance, and service availability.
• Support incident response, root-cause analysis, and preventive remediation.
• Implement reliability practices including service-level indicators (SLIs), service-level objectives (SLOs), backup, disaster recovery, and high availability.

5. Cloud Cost Optimization & FinOps

• Monitor cloud resource utilization and expenditure using AWS Cost Explorer, AWS Cost and Usage Reports (CUR), or equivalent cloud cost-management services.
• Identify cost optimization opportunities through resource rightsizing, autoscaling, storage lifecycle policies, and capacity planning.
• Implement cost allocation tags, budgets, and automated cost alerts.
• Collaborate with engineering and finance teams to improve cloud cost efficiency without compromising reliability.

6. Security, Compliance & DevSecOps

• Integrate security controls into CI/CD pipelines, including static application security testing (SAST), dependency scanning, infrastructure scanning, and container image scanning.
• Implement IAM best practices, least-privilege access, secrets management, encryption, and infrastructure hardening.
• Support vulnerability remediation, patch management, and compliance automation.
• Contribute to security requirements aligned with applicable enterprise policies and standards such as ISO 27001 and SOC 2.

7. AI-Assisted DevOps & AI Infrastructure Support

• Use AI-assisted development tools such as GitHub Copilot, Amazon Q Developer, or equivalent solutions to improve scripting, troubleshooting, and automation productivity.
• Support deployment and operational management of AI/ML applications and services.
• Collaborate with AI/ML engineering teams to automate AI application deployment workflows.
• Familiarity with MLOps concepts, model deployment pipelines, and AI workload monitoring will be an advantage.

8. Cross-Functional Collaboration & Platform Engineering

• Collaborate with application developers, AI engineers, QA teams, cloud architects, cybersecurity specialists, and infrastructure administrators.
• Build standardized infrastructure templates, deployment workflows, and reusable engineering components.
• Support customer environments across enterprise, SMB, and startup segments.
• Maintain technical documentation, operational runbooks, and infrastructure architecture diagrams.

Required Skills & Qualifications

Education & Experience

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience.
• 3–5 years of relevant experience in DevOps, cloud engineering, infrastructure automation, or related roles.
• Demonstrated hands-on experience implementing and supporting production cloud infrastructure and deployment pipelines.

Technical Competencies

• Cloud: AWS preferred; Azure or GCP experience advantageous.
• CI/CD: GitHub Actions, GitLab CI/CD, Jenkins, AWS CodePipeline, or Azure DevOps.
• IaC: Terraform, AWS CloudFormation, Ansible, or Pulumi.
• Containers: Docker, Kubernetes, Helm, Amazon EKS, or equivalent services.
• Programming: Python, Bash, or PowerShell.
• Observability: CloudWatch, Prometheus, Grafana, OpenTelemetry, or equivalent tools.
• Version Control: Git, GitHub, or GitLab.
• Operating Systems: Linux/Unix administration, networking fundamentals, and troubleshooting.
• Security: IAM, secrets management, vulnerability scanning, and DevSecOps fundamentals.
• FinOps: Cloud resource utilization monitoring, cost reporting, and optimization fundamentals.

Preferred Qualifications

• AWS Certified DevOps Engineer – Professional, AWS Certified Solutions Architect – Associate, Certified Kubernetes Administrator (CKA), or Terraform certification.
• Experience supporting hybrid or multi-cloud environments.
• Experience with GitOps tools such as Argo CD or Flux.
• Familiarity with AI-assisted coding tools and MLOps platforms.
• Experience working in customer-facing consulting or managed services environments.
• Familiarity with enterprise security, compliance, and operational governance requirements.