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Senior Software Engineer - Systems & Edge (Real-Time)

Derq - Dubai, United Arab Emirates - In-office - posted 2026-08-04

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Derq is an MIT spinoff building AI-powered traffic safety and smart infrastructure solutions. The company leverages real-time data from connected sensors (cameras, radar, traffic signal controllers) to predict and prevent road incidents, deploying edge and cloud solutions that make intersections and highways safer. As a Senior Software Engineer, you'll design and develop production-grade software systems across edge and cloud environments, with approximately 75% focus on real-time systems and 25% on application development. Key responsibilities include: - Design, develop, and maintain production-grade software systems across edge and cloud environments - Build and optimize real-time data processing pipelines and system services supporting live traffic deployments - Develop and maintain backend services, REST APIs, and integrations with third-party platforms - Contribute to internal web applications, dashboards, and operational tools for monitoring and managing deployed systems - Integrate software with sensors, cameras, traffic controllers, and other edge devices - Profile, debug, and optimize system performance across application, OS, and networking layers - Troubleshoot and resolve complex production issues in distributed and real-time environments - Improve system observability through logging, monitoring, diagnostics, and performance tracking - Build and maintain CI/CD pipelines, deployment workflows, and automation tooling - Collaborate with ML, QA, deployment, and product teams Required qualifications: 8+ years software engineering experience, strong C++ and/or Python skills, solid Linux development experience, backend services and REST API development, third-party API integration experience, multithreading and concurrency expertise, networking fundamentals (TCP/IP, DNS, routing), Git and CI/CD proficiency. Preferred: cloud platforms, containerized applications, distributed systems, edge computing, embedded Linux, hardware integration, IoT systems, frontend technologies, computer vision pipelines, or ML-powered systems experience.

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