Job Description

Job Title: Cloud Engineer - AWS, CI/CD & Infrastructure Automation

Department:

Information Technology / Research Computing

Location:

Bangalore/Kochi/Pan india

Shift: General

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.