Network Engineer/Developer Linux, ORAN, RIC, xApps, remote

Posted 2 days 6 hours ago by Sanderson

Permanent
Not Specified
Other
Somerset, Bristol, United Kingdom, BS483
Job Description

Network Engineer/Developer (Linux), ORAN, RIC, xApps

This assignment has been deemed OUTSIDE OF IR35.

Our client, an established and well know organisation based in central Bristol is looking to hire an experienced network and virtualisation engineer to support a high profile project utilising cutting edge technology.

The successful candidate will come from a background as a network engineer progressing in Development, specifically around Linux systems.

Essential is knowledge of OpenRan, xApps development, knowledge of RIC and developing Linux kernel drivers.

This is a hands on engineering and development role but will require extensive collaboration with cross-functional teams to design and implement cloud-based solutions, ensuring seamless integration with existing systems and infrastructure.

This assignment has been deemed OUTSIDE OF IR35.

Service can be provided on a predominantly remote basis - 2 days per month on site minimum.

General responsibilities: -

  • Design & implement tools for network equipment management focusing on low-latency and high bandwidth including low-level near real-time control loops, OpenRAN-style xApps development
  • Design & implement software agents for communication with network equipment
  • Develop and install Linux kernel drivers and modules
  • Deploy and fine-tune multi-path protocols such as MultiPath-TCP
  • Troubleshoot and resolve complex technical issues related to network optimization and wireless technology integration.
  • Knowledge of networking fundamentals, including TCP/IP, DNS, DHCP, VPN, and routing protocols.

Desirable skills include: -

  • Network/telecom engineering, with experience in 4G/5G.
  • General understanding of virtualised network infrastructure and edge computing
  • Experience in automation and programming.
  • Hands-on experience with containerization technologies, including Docker and/or Kubernetes, for deploying and managing containerized applications.
  • Basic understanding of AI and ML workloads.