Backend Developer

About the Role

We are seeking a Backend Developer with strong expertise in Go and Python to design and maintain the server-side infrastructure powering our edge AI and IoT systems. You will build scalable microservices, manage high-throughput video storage and indexing, and ensure secure, reliable communication with edge devices. This role requires deep knowledge of databases, distributed systems, and real-time communication, with optional DevOps exposure for deployment in cloud and on-prem environments.

Responsibilities

• Design and implement scalable backend services in Go and Python.
• Develop and maintain microservices for video storage, indexing, event processing, and notifications.
• Work with databases (MongoDB, PostgreSQL) including sharding, replication, and query optimization.
• Manage caching and messaging systems using Redis (pub/sub, caching, streams).
• Handle video storage and retrieval pipelines using MinIO (S3-compatible object storage).
• Build and secure REST APIs and WebSocket-based services for communication with edge devices and clients.
• Implement authentication, authorization, and security protocols (JWT, TLS, RBAC, OAuth2).
• Collaborate with frontend, edge, and AI teams to deliver end-to-end system functionality.
• (Optional) Support deployment using Docker, Kubernetes, and CI/CD pipelines.

Requirements

• 4+ years building backend systems in Go and Python.
• Strong knowledge of microservices architecture and concurrency patterns in Go/Python.
• Hands-on with MongoDB, PostgreSQL (sharding, replication) and Redis (pub/sub, caching, streams).
• Experience with MinIO or S3-compatible object storage for video systems.
• Solid understanding of HTTP, REST APIs, and WebSockets.
• Strong knowledge of JWT, TLS, RBAC, and OAuth2 best practices.
• Experience profiling and tuning high-throughput backends.

Nice to Have

• Experience with video storage/indexing systems (time-series, metadata, search).
• Familiarity with Kafka or RabbitMQ for event-driven systems.
• Knowledge of DevOps practices with CI/CD pipelines, Docker, Kubernetes.
• Exposure to monitoring tools (Prometheus, Grafana, ELK stack).
• Background in IoT or surveillance systems.