Python Backend Engineer
Nermin AlsheikhUAESENIORPosted 5d ago
PythonREST APIsDistributed systemsLLM integrationFastAPIasyncioKafkaRedisRabbitMQDockerKubernetesTerraform
About the Role
We are looking for an experienced Python Backend Engineer with strong expertise in enterprise platform engineering, distributed systems, data-intensive architectures, and LLM integration. This role focuses on designing, building, and owning scalable, reliable, production-grade backend services for complex enterprise environments.
Key Responsibilities
• Design and develop scalable enterprise backend platforms using Python
• Build high-performance APIs, asynchronous services, and distributed systems
• Integrate LLMs into enterprise applications and AI-powered workflows
• Design reliable data processing pipelines with traceability and data lineage
• Build multi-tenant platforms with strong customer isolation and resource management
• Implement scalable architectures capable of handling high traffic and demanding workloads
• Ensure reliable event processing, idempotency, fault tolerance, and system resilience
• Troubleshoot complex production issues and optimize system performance
• Support cloud, on-premises, and air-gapped deployments
• Lead architecture discussions, technical reviews, and engineering best practices
Requirements
• 5-8+ years of backend engineering experience with strong hands-on Python expertise
• Proven experience designing enterprise-grade platforms and distributed systems
• Strong knowledge of Python, asynchronous programming, REST APIs, and backend architecture
• Hands-on experience with scalable data pipelines, data provenance, or data lineage
• Strong understanding of multi-tenant architecture, workload isolation, and resource management
• Experience with concurrency, caching, queues, rate limiting, retries, and idempotency
• Strong system design skills with the ability to evaluate architectural trade-offs
• Experience with production monitoring, observability, performance tuning, and incident management
• Experience with cloud and on-premises enterprise environments