Backend/DevOps Engineer

2 days ago

Mumbai, Maharashtra, India Umang Global Group Pvt Ltd Full time ₹ 9,00,000 - ₹ 12,00,000 per year

About the Role

We are looking for a Backend/DevOps Engineer to build and maintain high-performance backend services and deployment pipelines for our AI-driven applications. You will design robust APIs, manage real-time data flows, and ensure reliable system deployment and monitoring. This role involves close collaboration with AI/ML, data, and frontend teams to deliver scalable, secure, and production-ready systems.

Key Responsibilities

  • Design and implement backend APIs (FastAPI/Flask/Django) for managing data, user profiles, and real-time events.
  • Develop services to handle real-time data streams and ensure low-latency delivery to frontend applications.
  • Integrate ML inference services with databases and business logic.
  • Deploy and orchestrate system components (streaming services, ML models, databases, frontend) on local or cloud infrastructure.
  • Containerize applications with Docker and manage orchestration (Docker Compose / Kubernetes).
  • Set up CI/CD pipelines for smooth deployments and updates.
  • Monitor system performance, uptime, and resource usage across compute environments.
  • Implement authentication, authorization, and data security best practices.
  • Troubleshoot backend and infrastructure issues to ensure smooth operation.

Requirements

Technical Skills:

  • Strong experience with backend frameworks: FastAPI, Flask, or Django.
  • Solid understanding of REST APIs / WebSockets / gRPC.
  • Good knowledge of databases: PostgreSQL, MySQL, MongoDB, or Redis.
  • Familiarity with real-time data or media streaming protocols (RTSP, WebRTC, HLS, FFmpeg, GStreamer).
  • Hands-on experience with Docker (mandatory), Kubernetes (preferred).
  • Strong Linux deployment skills.
  • Experience in CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins).
  • Knowledge of security, authentication, and access control mechanisms.

Nice to Have:

  • Exposure to AI/ML model serving or edge deployments.
  • Experience with monitoring tools (Prometheus, Grafana).
  • Understanding of performance optimization for real-time systems.

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