Sr Devops Engineer

* Deploy and maintain company websites and HRM Cloud applications.

* Configure and manage cloud servers and Linux environments.

* Set up CI/CD pipelines using GitHub/GitHub Actions.

* Configure domains, DNS, SSL certificates, and HTTPS.

* Deploy frontend, backend/API, and database services.

* Configure production and staging environments.

* Manage Docker containers where required.

* Monitor server performance, uptime, logs, and application health.

* Implement regular database and server backups.

* Maintain security, access controls, firewalls, and server permissions.

* Troubleshoot deployment, server, network, and application issues.

* Work closely with Full-Stack Developers and QA teams.

* Maintain deployment documentation and technical procedures.

Required Skills

* AWS / Azure / DigitalOcean or equivalent cloud platform

* Linux server administration

* Git & GitHub

* CI/CD and GitHub Actions

* Docker

* Nginx / Apache

* DNS & domain configuration

* SSL/TLS and HTTPS

* Database deployment and backup

* Basic networking and security

* Monitoring and troubleshooting

* Experience deploying web applications to production

Preferred Skills

* Kubernetes

* Terraform / Infrastructure as Code

* Cloud security

* Load balancing

* Redis / caching

* PostgreSQL / MySQL / MongoDB

* Experience with Node.js, React, PHP/Laravel, or .NET applications

What We Offer

* Opportunity to work on HRM Cloud and SaaS products

* Exposure to real-world cloud infrastructure and production systems

* Remote/hybrid working opportunity

* Growth opportunities within the technology team

* Opportunity to work with an international product-focused company

How to Apply

Send your CV,GitHub profile, LinkedIn profile, and details of your previous cloud/DevOps projects.

Subject: Application – DevOps & Cloud Engineer

About the Role

We are looking for an experienced AWS DevOps Engineer with around 4 years of hands-on experience to join our infrastructure/DevOps team. The ideal candidate will independently design, deploy, and maintain cloud infrastructure primarily on AWS, drive automation initiatives, mentor junior engineers, and work closely with cross-functional teams to build scalable, secure, and highly available systems. Exposure to Azure is a strong plus.

Key Responsibilities

·      Design, deploy, and maintain robust, scalable, and secure infrastructure on AWS

·      Architect and manage core AWS services such as EC2, S3, VPC, IAM, RDS, Lambda, ECS/EKS, Route 53, and CloudFront

·      Build, own, and optimize CI/CD pipelines (e.g., CodePipeline, Jenkins, GitLab CI, GitHub Actions) to enable fast and reliable deployments

·      Design and implement Infrastructure as Code (IaC) using Terraform / AWS CloudFormation

·      Set up and manage monitoring, logging, and alerting solutions (CloudWatch, ELK, Prometheus, Grafana, Datadog, etc.)

·      Implement and enforce security best practices including IAM policies, security groups, NACLs, KMS, Secrets Manager, and compliance standards

·      Lead troubleshooting and root cause analysis for infrastructure, deployment, and production incidents

·      Drive backup, disaster recovery, high-availability, and cost-optimization strategies (Reserved Instances, Savings Plans, right-sizing)

·      Containerize applications and manage orchestration using Docker, ECS, and/or Kubernetes (EKS)

·      Automate repetitive operational tasks through scripting and tooling

·      Support any hybrid or multi-cloud initiatives involving Azure services, where applicable

·      Mentor junior engineers and review their work, providing technical guidance

·      Collaborate with development, QA, security, and product teams to support and streamline application deployments

·      Maintain comprehensive documentation of architecture, configurations, processes, and runbooks

·      Participate in on-call rotations and incident response as needed

Required Skills & Qualifications

·      Bachelor's degree in Computer Science, IT, or a related field (or equivalent practical experience)

·      4+ years of hands-on experience working with AWS cloud services in a production environment

·      Strong expertise in core AWS services: EC2, S3, VPC, IAM, RDS, Lambda, CloudWatch, ECS/EKS, Route 53, ELB/ALB, Auto Scaling

·      Solid understanding of networking concepts (subnets, routing, security groups, load balancers, VPNs, VPC peering, Direct Connect)

·      Strong scripting/programming skills in Python, Bash, or PowerShell for automation

·      Hands-on experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation

·      Proven experience with Linux and/or Windows server administration

·      Strong understanding of CI/CD pipelines, Git-based version control, and branching strategies

·      Solid experience with containerization and orchestration (Docker, ECS, or EKS/Kubernetes)

·      Experience with configuration management tools (Ansible, Chef, or Puppet) is a plus

·      Application Server Management — strong knowledge of networking, firewalls, load balancers, Nginx, Apache, etc.

·      Ability to independently read, interpret AWS documentation, and troubleshoot complex issues

·      Experience with cost optimization, security audits, and compliance frameworks (e.g., ISO, SOC2) is a plus

·      AWS certification (Solutions Architect Associate/Professional, DevOps Engineer Professional) preferred

Good to Have

·      Working knowledge of Microsoft Azure services (Virtual Machines, VNets, Azure DevOps, Azure Storage, Azure AD/Entra ID, AKS)

·      Experience with multi-cloud or hybrid-cloud environments

·      Familiarity with Azure Resource Manager (ARM) templates or Bicep

·      Any Azure certification (AZ-104, AZ-400, etc.)

Soft Skills

·      Strong analytical, problem-solving, and decision-making ability

·      Excellent verbal and written communication skills

·      Ability to mentor and guide junior team members

·      Proactive, ownership-driven approach to infrastructure and incident management

·      Strong collaboration skills in a cross-functional, team-oriented environment

·      High attention to detail with a focus on reliability and scalability

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

Preferred Skills

• Experience supporting AI/GenAI, chatbot, or multi-agent platforms.
• AWS Certifications (Associate/Professional).
• Banking or Financial Services domain experience.

Job Description:

Pre-requisite skills required for a DevOps Engineer role include:

• 6+yrs exp in DevOps
• Experience working on Linux based infrastructure
• knowledge in AWS, docker, CI/CD tools
• Hands on exp in Python/shell scripting language
• hands on exp in AWS and Azure
• Work exp in Docker, Terraform, Ansible, Kubernetes, LINUX
• Excellent understanding of Ruby, Python, Perl, and Java
• Configuration and managing databases such as MySQL, Mongo
• Excellent troubleshooting
• Working knowledge of various tools, open-source technologies, and cloud services

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

We are looking for an experienced AWS DevOps Engineer with 5–7 years of experience in cloud infrastructure management, automation, and deployment engineering. The candidate should have strong hands-on experience with AWS services, Infrastructure as Code (IaC), CI/CD pipeline implementation, Jenkins, and Ansible.

• Design, implement, and maintain AWS cloud infrastructure and services.
• Build, manage, and optimize CI/CD pipelines using Jenkins.
• Automate infrastructure provisioning and management using Terraform or AWS CloudFormation.
• Develop and maintain Ansible playbooks for configuration management and automation.
• Manage AWS services such as EC2, S3, VPC, IAM, EBS, ELB, Auto Scaling, Route 53, and CloudWatch.
• Implement cloud infrastructure security, access management, monitoring, and backup strategies.
• Automate deployment processes and improve application release efficiency.
• Monitor infrastructure performance and troubleshoot cloud-related issues.
• Manage networking components, including VPC, subnets, routing, security groups, NACLs, DNS, VPN, and load balancers.
• Manage VMware virtualized environments and perform server administration activities.
• Perform Linux and Windows server administration, patching, upgrades, and troubleshooting.
• Collaborate with development and infrastructure teams to improve system reliability and operational efficiency.

Role Overview

We are looking for a DevOps / Platform Engineer with 3–4 years of experience to help manage AWS cloud infrastructure, automation, and AI-ready platform operations. You will work closely with engineering and AI teams to ensure scalable, secure, and reliable deployments.

Key Responsibilities

1. AWS & Infrastructure: Manage core AWS services (EC2, EKS, Lambda, RDS, S3, VPC) using Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
2. AI/ML Workflows: Support infra for AI applications, model serving, vector databases, and GPU-based workloads.
3. CI/CD & Automation: Build and maintain deployment pipelines using GitHub Actions, GitLab CI, or Jenkins.
4. Containers & Kubernetes: Deploy and maintain containerized applications using Docker and Kubernetes (EKS) or ECS.
5. Observability & Incident Support: Maintain dashboards and alerts with CloudWatch, Prometheus, or Grafana, and participate in on-call response.
6. Security & FinOps: Apply AWS security best practices (IAM, encryption, secrets) and assist with cloud cost optimization.

Must-Have Skills & Qualifications

1. 3–4 years of experience in DevOps, SRE, or Cloud Infrastructure Engineering.
2. AWS & Containers: Good working knowledge of core AWS services, Docker, and Kubernetes (EKS).
3. Infrastructure-as-Code: Practical experience with Terraform, CloudFormation, or AWS CDK.
4. Linux & Networking: Solid fundamentals in Linux systems, DNS, routing, and load balancing.
5. Scripting: Hands-on scripting proficiency in Python, Bash, or Go.
6. CI/CD & Observability: Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) and using monitoring tools (CloudWatch, Prometheus, Grafana, or Datadog).

Nice-to-Have Skills

1. Basic exposure to AI/ML infrastructure, model serving, or GPU-based compute.
2. Experience with event-driven messaging systems (Kafka, Redis, or SQS).
3. Familiarity with GitOps tools and Helm (ArgoCD, Flux, or OpenTelemetry).
4. AWS Certifications (Solutions Architect Associate, SysOps Administrator, or DevOps Engineer).

TECHJAYS

THE AI REIMAGINATION COMPANY

Position DevOps Lead

Experience 10+ Years

Location Coimbatore / Hybrid

Joining Immediate / ASAP

Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability

Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.

Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.

We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.

The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.

You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.

This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.

Key Responsibilities

1. Cloud Infrastructure & Architecture

• Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
• Own cloud infrastructure architecture and operations across AWS or Azure.
• Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
• Establish infrastructure standards, architecture patterns, and operational best practices.
• Manage cloud resource provisioning, configuration, scaling, and environment management.
• Ensure infrastructure meets requirements for availability, performance, security, and reliability.
• Drive infrastructure improvements through automation and continuous optimization.

2. DevOps & CI/CD Engineering

• Design, implement, and maintain CI/CD pipelines for application development and deployment.
• Manage multi-stage deployment workflows across development, testing, staging, and production environments.
• Implement automated build, testing, deployment, and release processes.
• Establish reusable pipeline templates, deployment standards, and approval workflows.
• Manage deployment strategies, including rolling, blue/green, and canary deployments.
• Implement rollback mechanisms and ensure reliable production releases.
• Integrate CI/CD workflows with source control, artifact repositories, and container registries.
• Continuously improve deployment efficiency, release reliability, and engineering productivity.

3. Containerization & Kubernetes Management

• Architect and manage containerized application environments using Docker and Kubernetes.
• Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
• Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
• Work with Helm charts for application packaging and deployment.
• Optimize container resource utilization, application scaling, and cluster performance.
• Troubleshoot complex container and Kubernetes-related production issues.
• Establish best practices for container security and workload reliability.

4. Infrastructure as Code & Automation

• Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
• Automate infrastructure provisioning, configuration management, and environment setup.
• Develop reusable infrastructure modules and deployment automation workflows.
• Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
• Reduce manual intervention through standardization and automation.
• Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

• Establish centralized monitoring, logging, alerting, and observability across cloud environments.
• Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
• Monitor application availability, infrastructure health, resource utilization, and system performance.
• Lead troubleshooting and resolution of complex production incidents.
• Conduct root cause analysis and implement permanent corrective actions.
• Establish operational practices for backup, disaster recovery, availability, and business continuity.
• Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

• Implement cloud security best practices across infrastructure and application environments.
• Manage IAM, RBAC, access controls, service identities, and secrets management.
• Secure cloud networking, virtual networks, firewalls, and infrastructure access.
• Implement container security and infrastructure hardening practices.
• Ensure cloud environments follow organizational security and compliance requirements.
• Identify infrastructure vulnerabilities and coordinate remediation activities.
• Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

• Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
• Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
• Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
• Support the infrastructure requirements of AI applications across development, testing, and production environments.
• Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
• Evaluate infrastructure technologies and tools that support evolving AI application requirements.

8. Technical Leadership & Team Development

• Provide technical leadership to DevOps engineers and guide implementation across projects.
• Establish engineering standards, infrastructure best practices, and operational procedures.
• Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
• Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
• Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
• Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

• 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
• Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
• Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

• Strong experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
• Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
• Experience implementing deployment automation and rollback strategies.
• Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

• Strong hands-on experience with Docker and Kubernetes.
• Practical experience managing EKS or AKS environments.
• Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
• Experience with Helm and container orchestration.
• Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

• Strong experience with Terraform and Infrastructure as Code practices.
• Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
• Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
• Strong understanding of Linux administration and system troubleshooting.

5. Monitoring & Reliability Engineering

• Experience implementing infrastructure and application monitoring.
• Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
• Understanding of incident management, root cause analysis, performance optimization, and system availability.
• Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

• Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
• Understanding of infrastructure requirements for deploying and operating AI-powered applications.
• Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.

Preferred Skills

• Experience implementing GitOps workflows using Argo CD or similar tools.
• Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
• Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
• Experience with cloud cost optimization and FinOps practices.
• Familiarity with AI/ML infrastructure and production GenAI applications.
• Experience with Python-based automation and infrastructure tooling.
• Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

• Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
• Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
• Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
• System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
• Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
• Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
• Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
• AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
• Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

What We Offer

• Competitive compensation aligned with experience and expertise.
• Coimbatore office-based work environment with hybrid flexibility.
• Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
• Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunities to influence infrastructure architecture and engineering practices.
• A culture that values clarity, integrity, ownership, and continuous growth.

Join Techjays

If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.

• 3 years of relevant experience in DevOps, Site Reliability Engineering (SRE), cloud operations, or application production support.
• Strong practical understanding of AWS cloud services, including compute, storage, IAM, networking, security, and monitoring.
• Good Linux administration skills, including system troubleshooting, performance analysis, log investigation, and service management.
• Hands-on experience with GitLab CI/CD, including pipeline configuration, execution, troubleshooting, YAML files, variables, artifacts, and GitLab Runners.
• Mandatory hands-on experience with Infrastructure as Code (IaC), preferably Terraform, including infrastructure provisioning, configuration management, reusable modules, state management, and troubleshooting deployment issues.
• Working knowledge of Git, branching strategies, merge requests, and version control workflows.
• Good understanding of networking fundamentals, including DNS, TCP/IP, ports, routing, load balancers, and AWS security groups.
• Ability to systematically investigate and resolve infrastructure, application, and deployment issues using logs, metrics, monitoring tools, and dependency analysis.
• Working knowledge of Python or Shell scripting for operational automation and troubleshooting.
• Strong problem-solving skills, communication, collaboration, willingness to learn, and ownership of incidents through resolution.

Preferred Skills and Experience

• Basic SQL knowledge for application and database-related operational investigations.
• Experience with AWS monitoring and logging services, particularly Amazon CloudWatch.
• Familiarity with incident, problem, and change management processes in production environments.
• Exposure to operational automation, proactive monitoring, alert optimization, and root cause analysis (RCA).
• Understanding of cloud infrastructure best practices, including security, reliability, availability, and cost optimization.
• Experience supporting containerized applications using Docker, Kubernetes, or Amazon EKS would be an advantage.

Key Responsibilities

• Automate application deployments from Bitbucket to servers using CI/CD pipelines.
• Design and manage scalable, highly available AWS infrastructure.
• Implement Auto Scaling, ELB, and Route 53 for traffic management and high availability.
• Work with AWS services including IAM, RDS, DynamoDB, EC2, and other cloud services.
• Build and manage Docker containers and server images.
• Deploy and manage applications using Kubernetes.
• Implement Infrastructure as Code using Terraform, CloudFormation, or Ansible.
• Develop automation scripts using Python and Bash.
• Implement monitoring and logging using tools such as Prometheus, Grafana, and ELK.
• Integrate security and compliance practices into CI/CD pipelines.
• Optimize infrastructure for security, scalability, performance, and cost.

Required Skills

• 3+ years of experience in DevOps or a similar role.
• Strong knowledge of AWS beyond EC2.
• Hands-on experience with Jenkins or similar CI/CD tools.
• Experience with Docker and Kubernetes.
• Good understanding of Terraform/IaC and automation.
• Proficiency in Python and/or Bash scripting.
• Knowledge of DevSecOps, security, and compliance best practices.
• Strong troubleshooting and problem-solving skills.