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

Sanderson Recruitment Plc
Bristol
GBP 40,000 - 60,000
Job description

Job Description

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

This assignment has been deemed OUTSIDE OF IR35.

Our client, an established and well-known 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.

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

General responsibilities:

  1. 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.
  2. Design & implement software agents for communication with network equipment.
  3. Develop and install Linux Kernel drivers and modules.
  4. Deploy and fine-tune multi-path protocols such as MultiPath-TCP.
  5. Troubleshoot and resolve complex technical issues related to network optimization and wireless technology integration.
  6. Knowledge of networking fundamentals, including TCP/IP, DNS, DHCP, VPN, and routing protocols.

Desirable skills include:

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