AWS Devops Engineer

Company Description

CAPSULE MEDIA is a content integration solution company that connects and manages everything about video contents. We work from video production, creator training & management to promotional marketing. Our goal is to work toward one goal, by working together organically from all direction: train content creators, create quality contents and run marketing promotions.

Role Description

This is a part-time remote role for an AWS DevOps Engineer. As an AWS DevOps Engineer, you will be responsible for managing and operating production/stage/development environments, monitoring application performance, deploying updates, and improving automation. You will also need to work with the development team to optimize application workflows, security, and monitoring of application components.

Job Summary: We are seeking an experienced AWS DevOps Engineer with a strong proficiency in Python and specialised knowledge in GPU support to join our dynamic team. The ideal candidate. will possess a solid understanding of cloud computing, infrastructure automation, continuous integration/continuous deployment (CI/CD) pipelines, and expertise in leveraging GPU technology for enhanced computational capabilities. As an AWS DevOps Engineer, you will play a crucial role in designing, implementing, and maintaining scalable and secure cloud infrastructure with a focus on GPU-accelerated workloads to support our applications and services. Responsibilities:
 Cloud Infrastructure Management:Design, deploy, and manage scalable, highly available, and fault-tolerant AWS infrastructure.
 Utilize AWS services such as EC2, S3, RDS, Lambda, and others to optimize system architecture.
 Automation and Scripting:Develop automation scripts and tools using Python to streamline deployment and operational tasks.
 Implement Infrastructure as Code (IaC) using tools like AWS CloudFormation or Terraform.
 CI/CD Pipeline Implementation:Build and maintain CI/CD pipelines for applications, ensuring efficient and reliable delivery processes.
 Implement automated testing and deployment strategies to accelerate the release cycle.
 Monitoring and Logging:Set up monitoring and logging solutions to ensure the health and performance of the infrastructure.
 Respond promptly to incidents, troubleshoot issues, and implement solutions.
 Security and Compliance:Implement security best practices in the cloud environment, including access control and data encryption.
 Ensure compliance with industry standards and regulatory requirements.
 Collaboration and Communication:Collaborate with cross-functional teams to understand application requirements and provide scalable infrastructure solutions.
 Communicate effectively with team members and stakeholders regarding system status, project progress, and issue resolution.
 Documentation:Maintain clear and concise documentation for infrastructure configurations, processes, and procedures.
Python Scripting:
 Strong proficiency in Python programming language.
 Experience in developing Python scripts for automation and orchestration tasks in a DevOps context.
 Knowledge of Python libraries and frameworks relevant to infrastructure as code (IaC) and automation.

Qualifications:
 Bachelor's degree in Computer Science, Information Technology, or a related field
 Proven experience as a DevOps Engineer in an AWS environment.
 Strong proficiency in Python for automation and scripting.
 Solid understanding of cloud computing concepts and AWS services.
 Experience with containerisation technologies such as Docker and orchestration tools like Kubernetes.
 Familiarity with version control systems, preferably Git.
 Knowledge of continuous integration tools (e.g., Jenkins, CircleCI) and configuration management tools (e.g., Ansible).
 Excellent problem-solving and troubleshooting skills.
 Strong communication and collaboration skills.
Certifications (Preferred):
 AWS Certified DevOps Engineer
 AWS Certified Solutions Architect
 Relevant certifications in Python programming.
 NVIDIA GPU certifications.
Preferences: Experience / Knowledge on below GPU Acceleration & deployment topics:
 GPU acceleration and parallel computing, especially with NVIDIA GPUs.
 Knowledge of GPU programming frameworks such as CUDA or OpenCL.
 Familiarity with GPU-based libraries for machine learning, such as cuDNN and cuBLAS.
 deploying and managing GPU-accelerated machine learning models.
 Proficiency in using deep learning frameworks like TensorFlow or PyTorch on GPU infrastructure.
 Understanding of distributed training with GPUs for large-scale machine learning models.

As an AWS DevOps Engineer, you will need to be organized, self-motivated, and detail-oriented. You also need to have great communication skills to communicate and collaborate with cross-functional teams,