DevOps and AI Engineer

Job Description

Qualifications (Grouped by Domain & Intended Purpose)
1. Cloud Platforms
AWS
Azure
GCP

Purpose: Provisioning, managing, and scaling cloud infrastructure and services across multi-cloud environments.

2. Configuration Management
Ansible
Chef
Puppet

Purpose: Automating infrastructure configuration, provisioning, and ensuring system consistency.

3. Infrastructure as Code (IaC)
Terraform
CloudFormation

Purpose: Defining and managing infrastructure through code for automation, repeatability, and scalability.

4. Scripting & Automation
Python
Shell

Purpose: Automating operational tasks, building scripts, and supporting DevOps workflows.

5. CI/CD Tools
Jenkins
GitLab CI
CircleCI

Purpose: Continuous integration, testing, and automated deployment pipelines.

6. Containerization & Orchestration
Docker
Kubernetes

Purpose: Packaging applications into containers and managing scalable, distributed systems.

7. Version Control
Git

Purpose: Source code management, collaboration, and version tracking across development teams.

8. Monitoring & Logging
Prometheus
ELK Stack (Elasticsearch, Logstash, Kibana)

Purpose: System monitoring, observability, log aggregation, and performance tracking.

9. Machine Learning & Artificial Intelligence
TensorFlow
PyTorch
AI/ML Algorithm Development

Purpose: Designing, training, and deploying machine learning models and AI-driven systems.

10. System Architecture, Networking & Security
System Architecture Design
Networking and Security

Purpose: Designing scalable, secure, and resilient systems with strong security and networking practices.

Additional Requirement
Bachelor’s degree in Computer Science, Engineering, or related field