We are seeking a highly skilled Senior DevOps and Cloud Engineer to design, implement, and manage scalable cloud infrastructure and automated CI/CD pipelines across multi-cloud environments. The ideal candidate will have deep expertise in cloud-native architecture, container orchestration, infrastructure automation, and DevOps best practices.
This role will focus on building and maintaining secure, scalable, and highly available platforms across AWS and GCP, enabling faster software delivery, reliable infrastructure provisioning, and efficient operations.
The candidate will also contribute to AI/ML platform engineering, supporting deployment of GenAI and LLM workloads, while ensuring strong observability, security, and operational excellence
Key Responsibilities
Cloud Infrastructure & Architecture
Design and implement scalable, secure, and resilient cloud infrastructure across AWS and GCP environments.
Build and manage cloud-native platforms using Infrastructure-as-Code (IaC) tools such as Terraform.
Architect and maintain multi-tier applications and infrastructure provisioning across cloud environments.
Implement best practices for high availability, scalability, and disaster recovery.
DevOps & CI/CD Automation
Design and maintain automated CI/CD pipelines using tools such as Jenkins, GitHub Actions, and GitLab CI/CD.
Develop and maintain Jenkins pipelines and shared libraries to standardize deployment workflows.
Implement GitOps practices using tools like ArgoCD to enable automated application deployments.
Automate build, testing, and deployment processes to improve delivery speed and reliability.
Containerization & Kubernetes
Build and manage containerized environments using Docker and Kubernetes.
Deploy and manage Kubernetes clusters (including GKE) to support cloud-native applications.
Optimize container orchestration, scaling, and resource management for production workloads.
AI/ML Platform Engineering
Support infrastructure for AI/ML workloads and GenAI applications.
Build and manage custom Dataproc images and ML infrastructure on GCP.
Deploy LLM inference workloads on Kubernetes (GKE) and ensure scalable infrastructure support.
Monitoring, Observability & Reliability
Implement monitoring and alerting solutions using Prometheus, Grafana, and AWS CloudWatch.
Ensure system reliability through logging, performance monitoring, and incident response processes.
Continuously improve platform observability and operational insights.
Security & Compliance
Implement cloud security best practices including IAM, network security, and access controls.
Ensure infrastructure and CI/CD pipelines follow secure DevOps (DevSecOps) practices.
Maintain compliance with enterprise security policies and governance standards.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
7+ years of experience in DevOps, Cloud Engineering, or Infrastructure Engineering roles.
Strong hands-on experience with AWS and GCP cloud platforms.
Proven experience implementing Infrastructure-as-Code using Terraform.
Experience with containerization and orchestration using Docker and Kubernetes.
Strong expertise in CI/CD pipeline design and automation.
Proficiency in scripting languages such as Python, Shell, or Groovy.
We are seeking a highly skilled Senior DevOps and Cloud Engineer to design, implement, and manage scalable cloud infrastructure and automated CI/CD pipelines across multi-cloud environments. The ideal candidate will have deep expertise in cloud-native architecture, container orchestration, infrastructure automation, and DevOps best practices.
This role will focus on building and maintaining secure, scalable, and highly available platforms across AWS and GCP, enabling faster software delivery, reliable infrastructure provisioning, and efficient operations.
The candidate will also contribute to AI/ML platform engineering, supporting deployment of GenAI and LLM workloads, while ensuring strong observability, security, and operational excellence
Key Responsibilities
Cloud Infrastructure & Architecture
Design and implement scalable, secure, and resilient cloud infrastructure across AWS and GCP environments.
Build and manage cloud-native platforms using Infrastructure-as-Code (IaC) tools such as Terraform.
Architect and maintain multi-tier applications and infrastructure provisioning across cloud environments.
Implement best practices for high availability, scalability, and disaster recovery.
DevOps & CI/CD Automation
Design and maintain automated CI/CD pipelines using tools such as Jenkins, GitHub Actions, and GitLab CI/CD.
Develop and maintain Jenkins pipelines and shared libraries to standardize deployment workflows.
Implement GitOps practices using tools like ArgoCD to enable automated application deployments.
Automate build, testing, and deployment processes to improve delivery speed and reliability.
Containerization & Kubernetes
Build and manage containerized environments using Docker and Kubernetes.
Deploy and manage Kubernetes clusters (including GKE) to support cloud-native applications.
Optimize container orchestration, scaling, and resource management for production workloads.
AI/ML Platform Engineering
Support infrastructure for AI/ML workloads and GenAI applications.
Build and manage custom Dataproc images and ML infrastructure on GCP.
Deploy LLM inference workloads on Kubernetes (GKE) and ensure scalable infrastructure support.
Monitoring, Observability & Reliability
Implement monitoring and alerting solutions using Prometheus, Grafana, and AWS CloudWatch.
Ensure system reliability through logging, performance monitoring, and incident response processes.
Continuously improve platform observability and operational insights.
Security & Compliance
Implement cloud security best practices including IAM, network security, and access controls.
Ensure infrastructure and CI/CD pipelines follow secure DevOps (DevSecOps) practices.
Maintain compliance with enterprise security policies and governance standards.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
7+ years of experience in DevOps, Cloud Engineering, or Infrastructure Engineering roles.
Strong hands-on experience with AWS and GCP cloud platforms.
Proven experience implementing Infrastructure-as-Code using Terraform.
Experience with containerization and orchestration using Docker and Kubernetes.
Strong expertise in CI/CD pipeline design and automation.
Proficiency in scripting languages such as Python, Shell, or Groovy.