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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

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