About this role
Job Overview
We are looking for an experienced DevOps Engineer to deploy, maintain, and support containerized applications across edge GPU nodes and central servers for an integrated surveillance and command system.
The role focuses on reliable software deployment, GPU runtime compatibility, CI/CD automation, release management, system monitoring, and recovery of production environments. The ideal candidate should have hands-on experience with Docker, Linux, NVIDIA CUDA/TensorRT, and production deployment of containerized applications.
Key Responsibilities
- Maintain CI/CD pipelines for frontend applications, APIs, Python-based AI runtimes, and model artifacts.
- Build, package, and deploy Docker images for GPU-enabled servers and edge devices.
- Manage Docker Compose-based services, including APIs, video streaming, databases, object storage, and map services.
- Manage staged releases across development, staging, and customer environments.
- Monitor system health, GPU utilization, disk usage, logs, and application availability.
- Troubleshoot production issues involving video streams, GPU drivers, runtime compatibility, and model loading.
- Implement rollback procedures and maintain deployment runbooks for production incidents.
- Coordinate deployment schedules and configuration changes with customer IT teams.
- Manage application secrets, environment variables, credentials, and network configurations securely.
- Maintain backup and recovery procedures for PostgreSQL and S3-compatible storage.
- Version and manage AI model packages, engine files, and deployment configurations.
- Ensure reproducible deployments across customer sites with restricted network access.
Required Skills & Qualifications
- 3–7 years of experience in DevOps, Platform Engineering, or Site Reliability Engineering (SRE).
- Strong hands-on experience with Docker, multi-stage builds, container registries, and Docker Compose.
- Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI/CD, or Azure DevOps.
- Practical knowledge of Linux administration, systemd services, shell scripting, logging, and troubleshooting.
- Experience with NVIDIA GPU environments, CUDA, TensorRT, and NVIDIA Container Toolkit.
- Understanding of GPU driver compatibility, runtime dependencies, and JetPack constraints for NVIDIA Jetson devices.
- Experience managing application configurations, secrets, and environment-specific deployments.
- Knowledge of PostgreSQL, S3-compatible storage, backup, and restore procedures.
- Experience with release management, production monitoring, incident response, and rollback strategies.
- Ability to troubleshoot deployment issues and reproduce production environments for debugging.
- Strong problem-solving skills and production ownership.
Preferred Skills
- Experience deploying applications on NVIDIA Jetson or other edge computing platforms.
- Knowledge of Ansible, Terraform, Prometheus, and Grafana.
- Experience with air-gapped environments, restricted networks, and offline package or image registries.
- Familiarity with video streaming infrastructure, LiveKit, SFU, and TURN networking.
- Experience supporting defence, surveillance, or other security-sensitive deployments.
- Experience managing multi-site deployments and low-bandwidth software updates.
What We Are Looking For
- Candidates who have independently owned end-to-end CI/CD and production deployments.
- Professionals who can demonstrate real-world incident recovery and rollback experience.
- Engineers comfortable working with customer infrastructure and controlled deployment procedures.
- Candidates with strong documentation, troubleshooting, and release management skills.
**Interested candidates with hands-on DevOps and GPU deployment experience are encouraged to apply!**
Pay: ₹900,000.00 - ₹1,100,000.00 per year
Work Location: In person