Backend Engineer - Network Platform

Piper Companies is seeking a Backend Engineer - Network Platform to join a leading networking and network simulation technology organization for a long term open ended contract working fully remote EST hours. The ideal Backend Engineer - Network Platform will play a critical role in developing and enhancing an industry-leading network modeling and simulation platform, building backend services that orchestrate virtualized network topologies, manage virtual machine and container lifecycles, and provide scalable APIs for customers to design and test complex network environments. Responsibilities of the Backend Engineer - Network Platform:

• Develop and maintain backend services responsible for orchestrating virtualized network nodes including routers, switches, and firewalls utilizing virtualization and container technologies.
• Design, build, and maintain scalable, high-performance RESTful APIs that enable users to create, deploy, and manage network topologies programmatically.
• Integrate with virtualization platforms including QEMU, Libvirt, Docker, and Kubernetes to optimize resource utilization and simulation performance.
• Develop tools and services that support network automation workflows and infrastructure-as-code (IaC) testing initiatives.
• Optimize system performance, scalability, reliability, and concurrency across large-scale simulated environments.
• Collaborate with frontend developers, QA engineers, DevOps teams, and network architects to deliver new functionality and platform enhancements.
• Troubleshoot and resolve complex backend, networking, and virtualization-related issues.
• Contribute to CI/CD processes, automated testing, and software quality initiatives.

Qualifications of the Backend Engineer - Network Platform:

• 4+ years of backend software engineering experience with strong Python and/or Go development skills.
• Eligible to work in the U.S. and able to obtain and maintain an Active U.S. Government Secret Clearance.
• Hands-on experience with Linux systems programming, OS internals, and virtualization technologies including QEMU, Libvirt, Docker, and Kubernetes.
• Strong networking knowledge, including TCP/IP, Layer 2/Layer 3 switching, routing protocols, and network architecture.
• Experience designing, developing, and supporting RESTful APIs and backend services.
• Familiarity with network simulation/emulation platforms such as Cisco Modeling Labs (CML), GNS3, or EVE-NG.
• Experience with network automation tools (Ansible, Terraform, Netmiko, NAPALM), CI/CD pipelines, GitHub, Jenkins, pytest, and automated testing frameworks is preferred.
• Understanding of SDN and cloud-native applications
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field

Compensation for the Backend Engineer - Network Platform includes:

• Salary range: $105,000 - $145,000 annually depending on experience
• Comprehensive benefits package including medical, dental, vision, 401(k), paid time off, and additional wellness benefits

This job opens for applications on 08/14/2026. Applications for this job will be accepted for at least 30 days from the posting date. Keywords: Backend Engineer, Software Engineer, Python Developer, Go Developer, Golang, API Development, REST API, RESTful Services, Linux, Linux Systems Programming, Virtualization, QEMU, Libvirt, Docker, Kubernetes, Containers, Network Simulation, Network Emulation, Cisco Modeling Labs, CML, GNS3, EVE-NG, TCP/IP, Routing Protocols, Layer 2, Layer 3, Network Engineering, Network Automation, Infrastructure as Code, IaC, Ansible, Terraform, Netmiko, NAPALM, SDN, Software Defined Networking, Cloud Native, Microservices, Distributed Systems, Backend Development, Platform Engineering, DevOps, CI/CD, Jenkins, Groovy, GitHub, pytest, Automation Testing, Systems Engineering, Virtual Machines, Networking, Data Center Networking, Enterprise Networking, Scalability, High Availability, Performance Optimization, Concurrent Systems, Cloud Computing, API Design, Container Orchestration, CCNA, Computer Science