Overview
We are seeking a DevOps Engineer with strong platform engineering experience to design and manage CI/CD pipelines using GitHub Actions and support application deployments across a multi-cloud environment (AWS, Azure, GCP).
This role is focused on deployment, automation, and infrastructure, not application or AI model development. Exposure to AI-enabled applications is a plus, but DevOps expertise is the primary requirement.
Note: This role is focused on DevOps and CI/CD engineering. Candidates with primarily AI/ML or data science backgrounds without strong deployment and infrastructure experience will not be a fit.
Key Responsibilities
DevOps & CI/CD (PRIMARY FOCUS)
- Design and implement GitHub Actions CI/CD pipelines (required)
- Deploy applications across dev, UAT, and production environments
- Ensure repeatable, scalable, and reliable deployment processes
- Establish GitHub standards, governance, and best practices
Platform & Infrastructure Engineering
- Build and manage infrastructure using Terraform or similar IaC tools
- Support multi-cloud deployments (AWS, Azure, GCP)
- Configure and maintain containerized environments (Docker, Kubernetes)
- Ensure CI/CD runners/agents are properly configured and optimized
Automation & Reliability
- Automate build, test, and deployment workflows
- Improve deployment speed, consistency, and ease of use
- Implement monitoring, logging, and alerting for production systems
Security & DevSecOps
- Implement secure CI/CD practices within GitHub
- Manage secrets, access controls, and pipeline security
- Align with enterprise security standards
Nice to Have (Secondary / Non-Primary)
- Exposure to deploying AI/ML-enabled applications
- Familiarity with tools such as GitHub Copilot, ClaudeCode, or Google AI tools
- Understanding of MLOps concepts (model deployment, lifecycle)
👉 Note: This role does NOT involve building AI models or data science work.
Required Qualifications
- 5+ years in DevOps / Platform Engineering
- Strong experience with GitHub Actions (NOT Azure DevOps)
- Experience with multi-cloud environments (AWS, Azure, GCP)
- Hands-on experience with Docker and Kubernetes
- Experience with Infrastructure as Code (Terraform preferred)
- Strong scripting (Python, Bash, or similar)
