DWDM-IP Engineer
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DWDM-IP Engineer — We are looking for a Optical Network/DWDM-IP Engineer to own the lifecycle of our optical transport network and its integration with the IP/MPLS core.
- Amsterdam, Netherlands
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Job Summary
You will be responsible for operating a hybrid ecosystem of short-haul (DC interconnects), metro, and long-haul DWDM systems. This role requires a "Full-Stack Transport" mindset—where you understand the physics of the fiber, signal modulation and could overview the logic of the ip/MPLS part of network.
Job Responsibilities:
- Hybrid Infrastructure Management: Configure, deploy, and scale multi-vendor DWDM systems (Ciena, Nokia-Infinera, ADVA/Adtran) to support 400G/800G+ coherent interfaces.
- Operational Excellence: Lead the troubleshooting of complex optical-to-IP failures, ensuring minimal MTTR for critical backbone spans and DCI links.
- Network Evolution: Design and test new optical solutions, focusing on Open Line Systems (OLS), disaggregated hardware, and pluggable coherent optics (QSFP-DD/OSFP).
- Automation & Data Integrity: Build and maintain the "Source of Truth" (Netbox-based) for lambdas, channels, and dark fiber assets; participating in automate commissioning via Python/gNMI.
- Strategic Collaboration: Work with Data Center Ops and IP Engineering to align optical capacity with traffic engineering (SR-MPLS) demands.
- Vendor & Asset Management: Manage relationships with dark fiber providers and channel suppliers; monitor performance against SLAs.
We Expect You To:
- Deep Optical Expertise: Knowledge of ROADM networks and use-cases, optical amplification (EDFA/Raman), understand Coherent modulation formats and its characteristics in multi span long-haul scenarios.
- IP/MPLS Proficiency: Have an understanding of the IP/MPLS stack (any from BGP/OSPF/IS-IS) to perform initial debugs on packet-over-optical issues.
- Hands-on with Production Platforms: Direct experience with ADVA/Adtran platforms or Ciena /Nokia-Infinera
- Automation Mindset: good to read Python for automating routine of inventory synch
- Diagnostic Precision: Expert use of OTDR, OSA, and BERT equipment for characterization of short, middle, and long-haul fiber spans.
- Mobility: Willingness to travel to key sites in the USA/EU/APAC for critical hardware deployments and complex physical-layer audits.
Preferred Qualifications:
- Good in Linux-based network tools and telemetry for optical monitoring.
- Proven track record in network modernization projects (e.g., migrating from 100G to 400G/800G architectures).
- Nice to have Experience with MPLS and its interaction with optical layer performance metrics.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
Nebius provides AI cloud infrastructure, offering a full-stack cloud platform for AI developers, enterprises, and research institutes to build and deploy generative AI applications and train and run machine learning models in a secure, high-performance, and cost-optimized environment.