Staff Network Reliability Engineer (f/m/d)

IONOS EN; Berlin; On-site; EUR 110,000 - 150,000; Full time

Job summary

IONOS EN is seeking a Staff Network Reliability Engineer to own reliability across large production data center networks. You will lead incident response, drive automation, and apply AI to operations to detect anomalies and automate remediation.

The role emphasizes deep networking, observability, and collaboration with NRE teams to improve SLAs and reduce toil. Fluency in English is required; German is a plus. This is an on-site Berlin-based position with modern facilities.

Qualifications

• Extensive hands-on experience operating large-scale production data center networks (5+ years for Senior, longer for Staff).
• Strong Linux fundamentals and scripting with Python for automation.
• Experience with multi-vendor networks (Juniper, Cisco) and network tooling (NetBox).
• Familiarity with AI/ML-assisted operations and observability practices.

Responsibilities

• Own reliability of the physical fabric, SDN overlay, and virtual network functions across data centers.
• Lead major network incident responses and postmortems with lasting fixes.
• Reduce toil by automating pipelines and configuration tasks with NRE Automation.
• Apply AI to anomaly detection, diagnosis, remediation, and runbooks with prudent judgment.
• Strengthen observability and collaborate on capacity planning and lifecycle changes.
• Coordinate handovers with NRE Provisioning and share on-call duties.

Skills

Data center networking

L2/L3 routing

Linux fundamentals

Python scripting

AI in operations

Observability

Incident response

SLOs / reliability

English fluency

German language

Tools

Juniper

Cisco

SONiC

NetBox

GitLab CI/CD

Job description

Staff Network Reliability Engineer (f/m/d)

About IONOS

At IONOS, we don't just manage servers - we shape the digital future for more than 6.2 million customers worldwide with our solutions. As Europe's leading hosting provider and a pioneer in independent cloud solutions, we are building next-generation infrastructure - from sovereign cloud architectures and high-performance GPU clusters to integrated AI automation tools.

What drives us is digital sovereignty for Europe and real impact for small and medium-sized businesses (SMBs) as well as large enterprises. We work in agile teams, rely on transparent structures, and believe that excellence and innovation only emerge through true team spirit.

Ready for your next step? Become part of IONOS and grow with us.

NRE Operations runs the data center networks for the entire IONOS group: the physical fabric and underlay, the SDN overlay, and the virtual network functions on top, across dozens of data centers. We are looking for a senior or staff-level engineer who operates large production networks with a reliability mindset. You define what "healthy" means, catch problems before customers do, lead the hardest incidents, and partner with NRE Automation to push routine operations toward zero manual steps. AI is central to how we work, both to make the network smarter and to make each engineer faster.

We expect every engineer here to be fluent with AI, and we mean it in two concrete ways. First, applying AI to the network itself: anomaly detection, automated diagnosis and root-cause analysis, config generation and validation, smarter alerting, and runbook or agent-driven automation. Second, using AI to raise your own output: coding assistants and LLM tooling for scripting, troubleshooting, research, and documentation. Reliability work punishes blind trust, so the skill that matters most is judgment. You need to know when an AI-generated config or diagnosis is trustworthy and when it is not.

Tasks

• Own reliability of the physical fabric, SDN overlay, and virtual network functions across all IONOS data centers. Set service level objectives and drive down unplanned downtime.
• Lead incident response on major network incidents and run postmortems that produce lasting fixes.
• Remove toil through automation, working with NRE Automation on pipelines and tooling for lifecycle, patching, and service configuration.
• Apply AI to operations: anomaly detection, automated diagnosis, config generation and validation, and automated remediation, with the judgment to know when AI output is trustworthy.
• Strengthen observability so problems surface before they reach customers, and shape lifecycle, upgrade, change-management, and capacity practices.
• Collaborate with NRE Provisioning on clean handovers.
• Share the on-call rotation covering the above.

Qualifications

• Extensive hands-on experience operating large-scale production data center networks (5+ years for Senior, longer for Staff).
• Deep Layer 2 and Layer 3 knowledge: routing (BGP, OSPF) and VXLAN with BGP/EVPN.
• Multi-vendor operations across Juniper and Cisco; SONiC and Netbox familiarity is a plus.
• Strong Linux fundamentals and the toolkit that goes with them (bash, tcpdump, iptables, git).
• Network automation you have built, using Python with Ansible and CI/CD on GitLab.
• A reliability-engineering mindset: SLOs, observability, incident command, postmortems, designing out toil.
• Fluent, critical use of AI in daily engineering, plus a track record or credible ideas for applying AI to network operations.
• Fluent English for international teams; German is a plus. Ownership and a calm approach when things break.
• Flexible working hours through trust-based working hours.
• At some locations a subsidized canteen and various free drinks.
• Modern office space with very good transport connections.
• Various employee discounts for activities and products.
• Employee events such as summer and winter parties, as well as workshops.
• Numerous training and development opportunities.
• Various health offers, such as sports and health courses.

Application Note

We value diversity and welcome all applications - regardless of, for example, gender, nationality, ethnic or social origin, religion, disability, age as well as sexual orientation and identity, physical characteristics, marital status or any other irrelevant factor subject to applicable law.