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)

CBTS

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