Job Summary

We are looking for an experienced Senior DevOps Engineer with 8+ years of hands-on experience in designing, implementing, automating, and managing scalable cloud infrastructure and CI/CD pipelines on AWS.

The ideal candidate must have strong, practical expertise in AWS, AWS Cloud Development Kit (CDK), GitHub Actions, Amazon ECS, Amazon EKS, and AI usage and implementation. All these skills are mandatory, and candidates must demonstrate their hands-on application in their current or recent projects.

The candidate will be responsible for building and maintaining cloud-native infrastructure, implementing infrastructure as code (IaC), automating application deployments, managing containerized workloads, and leveraging AI capabilities to improve DevOps automation, operational efficiency, monitoring, and incident resolution.

The role requires a strong engineering mindset, troubleshooting capabilities, automation expertise, and the ability to independently drive DevOps initiatives in a production environment.

Key Responsibilities

1. AWS Cloud Infrastructure Management

- Design, deploy, configure, and manage scalable, highly available, and secure infrastructure on AWS.
- Work extensively with AWS services such as EC2, VPC, IAM, S3, ALB/NLB, Route 53, CloudWatch, CloudTrail, Systems Manager, and AWS Secrets Manager.
- Implement cloud networking, security controls, access management, monitoring, and cost optimization strategies.
- Configure auto-scaling, load balancing, fault tolerance, backup, and disaster recovery mechanisms.
- Troubleshoot infrastructure, networking, performance, and availability issues across development, staging, and production environments.
- Apply AWS Well-Architected Framework principles to improve reliability, security, operational excellence, and performance.

2. Infrastructure as Code AWS CDK

- Design, develop, deploy, and maintain AWS infrastructure using AWS Cloud Development Kit (CDK).
- Build reusable, modular, and maintainable infrastructure components using AWS CDK with TypeScript, Python, or another supported language.
- Create and manage CDK stacks, constructs, environments, and deployment configurations.
- Automate provisioning of AWS resources, including VPCs, IAM roles, ECS/EKS infrastructure, load balancers, and supporting services.
- Implement infrastructure version control, environment-specific configurations, and automated validation.
- Manage infrastructure changes through code reviews, testing, and controlled deployment processes.
- Troubleshoot CDK synthesis, deployment, permissions, and CloudFormation-related issues.

3. CI/CD Automation – GitHub Actions

- Design, implement, and maintain end-to-end CI/CD pipelines using GitHub Actions.
- Develop reusable workflows, composite actions, workflow templates, and automated deployment processes.
- Integrate source control, build automation, unit testing, security scanning, artifact management, and deployment stages.
- Automate application builds and deployments to Amazon ECS and Amazon EKS.
- Configure secure authentication between GitHub Actions and AWS,



preferably using OpenID Connect (OIDC) and short-lived credentials.
- Implement branch protection, pull request validation, approval gates, workplace controls, and release management.
- Integrate code quality tools, dependency scanning, container image scanning, and infrastructure security checks.
- Troubleshoot pipeline failures, deployment errors, build issues, and release bottlenecks.
- Optimize pipeline execution time, reliability, security, and developer productivity.

4. Containerization and Orchestration – Amazon ECS

- Design, deploy, and manage containerized applications using Amazon Elastic Container Service (ECS).
- Implement ECS services, tasks, task definitions, clusters, and deployment configurations.
- Work with AWS Fargate and/or ECS on EC2, based on project architecture.
- Configure Amazon Elastic Container Registry (ECR) for container image storage and version management.
- Implement application deployments using load balancers, service discovery, auto-scaling, and health checks.
- Configure task execution roles, task IAM roles, secrets, logging, and networking.
- Implement rolling deployments and, where appropriate, blue-green or canary deployment strategies.
- Monitor container health, resource utilization, application performance, and deployment stability.
- Troubleshoot container startup failures, networking issues, resource constraints, and production incidents

5. Kubernetes – Amazon EKS

- Design, deploy, configure, and operate production-grade Amazon Elastic Kubernetes Service (EKS) clusters.
- Manage Kubernetes deployments, pods, services, namespaces, ConfigMaps, Secrets, ingress resources, and persistent storage.
- Implement Helm charts and Kubernetes manifests for application packaging and deployment.
- Configure cluster networking, IAM integration, access controls, and workload permissions.
- Implement cluster and workload auto-scaling using suitable Kubernetes and AWS-native mechanisms.
- Manage node groups, cluster upgrades, workload availability, and resource allocation.
- Implement Kubernetes RBAC, network policies, secrets management, and container security best practices.
- Configure observability through CloudWatch, Prometheus, Grafana, or equivalent tools as required.
- Troubleshoot pod failures, scheduling issues, image pull errors, networking problems, resource limits, and cluster-level incidents.
- Implement secure and reliable application delivery pipelines from GitHub Actions to Amazon EKS.

6. AI Usage and Implementation in DevOps – Mandatory

- Demonstrate hands-on experience using AI tools and capabilities in real-world DevOps projects.
- Identify opportunities to integrate AI into CI/CD workflows, infrastructure automation, monitoring,



troubleshooting, and operational support.
- Use AI-assisted development tools to improve scripting, infrastructure code generation, workflow creation, code reviews, and documentation, with appropriate human validation.
- Implement AI-assisted analysis of application logs, infrastructure metrics, deployment failures, and operational incidents.
- Integrate AI-powered capabilities into automation workflows using suitable APIs, SDKs, services, or internal platforms.
- Evaluate and implement AI-based solutions to improve incident detection, root-cause investigation, anomaly analysis, and operational efficiency.
- Where relevant, leverage AWS AI services, Amazon Bedrock, or other enterprise-approved AI platforms to develop practical DevOps use cases.
- Implement appropriate guardrails for sensitive data, access control, output validation, security, and responsible AI usage.
- Measure the impact of AI implementation through improvements in deployment efficiency, troubleshooting time, automation coverage, or incident response

7. Monitoring, Reliability, Security, and Automation

- Implement monitoring, logging, alerting, and observability for cloud infrastructure and containerized applications.
- Use CloudWatch and relevant third-party monitoring tools to track system health and performance.
- Develop automation scripts using Python, Bash, or similar scripting languages.
- Implement DevSecOps practices, including secrets management, vulnerability scanning, access controls, and compliance checks.
- Participate in incident management, root-cause analysis, production troubleshooting, and preventive action planning.
- Establish operational standards, infrastructure documentation, deployment procedures, and recovery processes.
- Optimize cloud resource consumption, improve system reliability, and reduce repetitive manual operations

8. Collaboration and Technical Leadership

- Collaborate with application developers, architects, QA engineers, security teams, and infrastructure teams.
- Participate in architecture discussions, technical design reviews, code reviews, and release planning.
- Mentor junior engineers and promote DevOps automation and engineering best practices.
- Take ownership of assigned deliverables and independently resolve complex technical challenges.
- Ensure infrastructure and deployment solutions meet performance, security, availability, and maintainability requirements.

Mandatory Technical Skills

1. AWS Cloud: Strong practical experience designing, implementing, and supporting AWS infrastructure in production.
2. AWS CDK: Experience developing and deploying infrastructure as code using AWS CDK.
3. GitHub Actions: Experience building and maintaining CI/CD pipelines and reusable workflows.
4. Amazon ECS: Experience deploying and operating containerized applications on ECS.
5. Amazon EKS: Experience managing Kubernetes workloads and production deployments on EKS.
6. AI Usage and Implementation: Demonstrable experience applying AI tools, integrations, or AI-powered automation to real DevOps use cases.

📌 Devops Engineer (Hyderabad)
🏢 Feuji Software Solutions
📍 Hyderabad