We are looking for a hands-on DevOps Engineer to support mission-critical EO/IR surveillance and defence command systems involving real-time video processing, AI model deployment, GPU infrastructure and edge computing.
Experience: 3–7 Years Budget: Up to ₹12 LPA
What you'll work on:
- Deploying containerized surveillance applications across GPU-enabled servers and edge devices.
- Managing Docker images, CI/CD pipelines and versioned AI model/engine releases.
- Handling NVIDIA CUDA/TensorRT runtime compatibility and Jetson-class edge deployments.
- Maintaining Linux services, application health monitoring and production recovery.
- Implementing controlled software updates, rollback procedures and reproducible deployments in restricted defence IT environments.
Mandatory Skills:
Docker & Docker Compose
CI/CD — GitHub Actions, GitLab CI or Azure DevOps Linux administration and production troubleshooting Container image management and release engineering Deployment recovery and rollback procedures
Preferred: NVIDIA CUDA, TensorRT, Jetson, GPU deployments, Prometheus/Grafana, MinIO/S3 and Ansible/Terraform.
Ideal candidates: DevOps / Platform / SRE professionals who have owned production deployments of containerized products. Experience in defence, surveillance, video analytics, robotics, edge AI or other GPU-intensive systems will be an advantage.
Pay: ₹500,000.00 - ₹1,200,000.00 per year
Work Location: In person
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