Senior Backend Engineer - Full Cycle Retail Robotics Engineering

Role Overview As an engineer at Telexistence, you will not only design, develop, and maintain the core backend services for our robotic operations management system but also owns the end-to-end lifecycle of a product capability, from problem understanding and design to implementation, release, operation, measurement, and continuous improvement. You will drive technical strategy and architectural decisions, ensuring that our backend systems are scalable, secure, and cost efficient for our subscription-based enterprise solution. You will work closely with stakeholders such as business development, operations teams to translate business requirements into effective technical solutions, while managing projects and collaborating with stakeholders across the organization. Team & Platform Context We develop using C# (.NET) for both backend and edge communication services to ensure unified development across systems. Robots run ROS/C++ on NVIDIA Jetson AGX devices and connect to cloud services through gRPC and MQTT. You will work across this stack—implementing backend agents, on-device services, and deployment pipelines with Ansible and Docker—to deliver seamless cloud-to-edge operations. The Challenge: Software Meets Hardware Because our software applications (spanning both frontend and backend) serve as the direct interface for end-users, we face a constant stream of diverse and evolving requirements. You will work in a unique environment where software speed meets hardware reality: - Bridging the Cycle Gap: Hardware and Automation development cycles are inherently longer than pure software. You will often need to devise creative software workarounds to mitigate hardware issues or implement "virtual" features to validate business value before hardware is ready. - Elevating Engineering Standards: While teams in other specialized domains are experts in their fields, they may be less familiar with modern SaaS practices or non-functional requirements (NFRs). You will act as a bridge, supporting other teams with general software development know-how and ensuring the overall system is robust and scalable. This role requires more than just coding; it demands the flexibility to navigate constraints and the leadership to raise the bar for software engineering across the organization. Company-Wide Tech Stack - Frontend: TypeScript, React, C#, Blazor, (Tailwind, shadcn) - Backend: .NET - Cloud Infra: Terraform, Azure, Kubernetes - Data Stores: PostgreSQL, MongoDB, Redis - IoT/Edge: .NET, C++, Python, ROS, NVIDIA Jetson AGX, IoT boards - CI/CD: GitHub Actions, SonarQube, Ansible Requirements 6+ years of professional experience as a software engineer. 4+ years of hands-on experience with C#/.NET. Ability to read and write production-level C++. 3+ years of experience developing applications for real users, including release and operation phases. Experience in team development using Git with 5 or more engineers. Experience building software for edge or IoT devices running Linux (ARM64 preferred). Experience with containerized deployments (Docker) and remote provisioning (Ansible). Knowledge of gRPC, MQTT, WebSocket, or similar communication protocols. Experience integrating telemetry and monitoring systems for distributed environments. Comfortable collaborating with hardware and field operations teams, thriving in fast-paced environments, and open to occasional travel for on-site support. Nice to Have Robotics, computer vision, or automation systems experience. Knowledge of Azure IoT Hub, Azure Container Registry, or related cloud services. Familiarity with ROS/ROS2 concepts including nodes, topics, services, and launch files. Familiarity with web-based visualization and debugging tools. Background in performance optimization for real-time systems. Understanding of security and authentication mechanisms for device communication. Experience deploying robotics or large-scale IoT systems in production environments. Exposure to retail automation or supply chain technology. Experience deploying machine learning models on edge devices (TensorRT, ONNX).