Cloud Engineer

Job Description

Job Title: Cloud Engineer – AWS, CI/CD & Infrastructure Automation Department: Information Technology / Research Computing Location: Bangalore/Kochi Shift: Need clarity Job Type: Full-Time Reports To: Director of IT Infrastructure / Head of Research Computing Position Summary: DBiz.ai is seeking a dedicated and technically proficient Cloud Engineer to support our growing cloud infrastructure needs across academic, research, and administrative domains. The ideal candidate will have strong experience with AWS core services , CI/CD pipelines using GitHub , and Infrastructure as Code (IaC) to help modernize and automate our cloud environments. Key Responsibilities: Design, implement, and manage AWS-based cloud infrastructure to support academic and research computing needs. Develop and maintain CI/CD pipelines for deploying applications and services using GitHub Actions or similar tools. Automate infrastructure provisioning and configuration using IaC tools such as Terraform or AWS CloudFormation. Design and implement solutions using AWS Machine Learning (SageMaker, Bedrock), data analytics (Redshift), and data processing tools (Glue, Step Functions) to support automation and intelligent decision-making Collaborate with faculty, researchers, and IT staff to support cloud-based research workflows and data pipelines. Ensure cloud environments are secure, scalable, and cost-effective. Monitor system performance and troubleshoot issues related to cloud infrastructure and deployments. Document cloud architecture, workflows, and best practices for internal knowledge sharing and compliance. Required Qualifications: Bachelor’s degree in Computer Science, Information Technology, or a related field. Strong experience with AWS core services (EC2, S3, IAM, VPC, Lambda, CloudWatch, etc.). Proficiency in GitHub and building CI/CD pipelines . Hands-on experience with Infrastructure as Code tools (Terraform, CloudFormation, etc.). Familiarity with scripting languages (e.g., Python, Bash). Exposure to AWS Machine Learning services (e.g., SageMaker, Bedrock), Data Analytics tools (e.g., Redshift), and Data Processing and Orchestration services (e.g., Glue, Step Functions). Strong understanding of cloud security, networking, and architecture principles. Excellent communication and collaboration skills, especially in academic or research settings. Preferred Qualifications: AWS Certification (e.g., AWS Certified Solutions Architect – Associate). Experience supporting research computing environments or academic IT infrastructure . Familiarity with containerization (Docker, Kubernetes) and hybrid cloud environments. Experience working in a university or public sector environment.