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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - AI Platforms & Edge Computing - **Company:** Matrixspace, Inc. - **Location:** Burlington, MA, United States (Remote available) - **Experience:** Experienced - **Salary:** $125,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Build Automation, Microsoft Azure, Bash Shell, C++ (Programming Language), Software as a Service, Cloud Computing, CMake, Configuration Management, Continuous Integration, Data as a Services, Distributed Data Store, Distributed Systems, Middleware, Python (Programming Language), Machine Learning, Network Protocols, Cloud Services, Service-Oriented Architecture, Software Engineering, TCP/IP, Cloud Platform System, Real Time Systems, Delivery Pipeline, Backend, Git, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Low Latency, Real Time Data, Machine Learning Operations, Front End Software Development, Multiaccess Edge Computing, Api Design, Stream Processing, Docker, Golang - **Published:** June 10, 2026 - **Apply:** https://www.careerjet.com/jobad/us51c01b2cb07ad7355989a1ed39329c3f ## About the Role Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future. * 2-4 years of software engineering experience in embedded, cloud, or distributed systems. * Proficiency and recent experience coding in C/C++ required. * Strong knowledge of edge computing, AI platform development, or real-time data systems. * Experience building backend systems or APIs * Familiarity with cloud platforms (AWS, GCP, or Azure) * Understanding of basic distributed systems concepts (e.g., scalability, latency, reliability) * Ability to collaborate effectively and learn quickly in a fast-paced environment, * Experience with Go, and/or Python a plus. * Experience with containers or Kubernetes * Exposure to infrastructure-as-code or CI/CD pipelines * Interest in AI/ML systems or model deployment * Exposure to edge computing or real-time systems ## Description We're looking for a software engineer to help build and scale our edge and cloud platform for AI-powered applications. In this role, you'll work on backend services, distributed systems, and infrastructure that enable real-time data processing and intelligent decision-making at the edge. You'll collaborate closely with experienced engineers across platform, AI, and embedded systems, contributing to the design and implementation of scalable systems while growing your skills in edge computing and modern cloud infrastructure. This is not a fully remote role -- you will be required to be onsite at least a few days per week!, * Design and implement platform software supporting AI workloads, edge inference, and distributed data pipelines across hybrid environments. * Contribute to the architecture, design, and deployment of scalable systems in both cloud-based and on-premises runtime environments. * Develop and maintain high-performance components in C/C++, Go, and Python, optimized for edge and real-time environments. * Build and manage API-based middleware that connects AI models, data services, and frontend interfaces. * Implement service-oriented architectures (SOA) and Software-as-a-Service (SaaS) frameworks to support modular, extensible system design. * Leverage Infrastructure-as-Code (IaC) for automated provisioning, deployment, and configuration management. * Employ containerization (Docker) and orchestration (Kubernetes) for edge-to-cloud deployments and lifecycle management. * Integrate networking protocols (TCP/IP, HTTPS) for secure, high-throughput edge-cloud communication. * Use CMake and BASH scripting for build automation, testing, and deployment pipelines. * Collaborate using Git-based configuration management systems in a modern CI/CD environment. * Work closely with data scientists and AI engineers to embed ML models into production-grade edge systems. * Optimize performance, reliability, and scalability across resource-constrained and distributed computing environments. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Code to Road in < 12 hours](https://www.wearedevelopers.com/videos/1082-code-to-road-in-12-hours) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [The Future of Computing: AI Technologies in the Exascale Era](https://www.wearedevelopers.com/videos/1106-the-future-of-computing-ai-technologies-in-the-exascale-era) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)