Senior Network Production Operations Engineer

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack - from electrons to tokens - to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that - with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved - people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

About This Role:
Crusoe Cloud is seeking a Senior Network Production Operations Engineer to support production reliability across our global network infrastructure, including edge, backbone, data center fabric, and GPU cluster interconnects. This is a hands-on production role focused on incident response, root cause analysis, and automation-driven operational execution that keeps our hyperscale AI infrastructure running at scale. Your work will directly affect the availability of AI workloads running across thousands of GPUs worldwide.

The ideal candidate is an experienced network engineer with solid operational experience in large-scale environments who thrives in high-pressure situations and takes pride in keeping systems healthy. You'll build automation to reduce operational toil, execute on established SLIs and SLOs, contribute to observability tooling, and serve as a responder during high-severity network events.

What You'll Be Working On:

• Production Reliability: Support uptime across Crusoe's global edge, backbone, data center, and GPU cluster network, directly supporting AI workloads at scale.

• Operational Automation: Write and maintain Python-based tooling to reduce toil, automate common remediation workflows, and speed up mean time to resolution across the operations org.

• Incident Response: Participate in high-severity network events - detection, triage, mitigation - and contribute to stakeholder communication and postmortem documentation.

• Root Cause Analysis: Perform RCAs using existing and newly built tooling, and help drive remediation items to closure.

• Observability: Build automation on top of Crusoe's monitoring stack (streaming telemetry, SNMP, NetFlow, Kentik, Grafana, Prometheus, ThousandEyes) to reduce manual triage and surface actionable signal faster.

• Operational Standards: Maintain and improve runbooks, escalation playbooks, and SOPs, flagging opportunities for scripting or automation.

• SLI/SLO Execution: Help build and maintain the automated dashboards and alerting that back reliability metrics, in partnership with Architecture and SRE teams.

• Collaboration: Work closely with Architecture and SRE teams to execute on operational excellence initiatives and improve day-to-day practices.

What You'll Bring to the Team:

• 5+ years of production network engineering experience with a focus on operations, incident response, and reliability in large-scale or internet-scale environments.

• Strong Python and scripting proficiency: comfortable writing diagnostic tooling and automation scripts, and extending existing automation pipelines.

• Hands-on experience with observability and monitoring tools including streaming telemetry, SNMP, NetFlow/sFlow, Grafana, Prometheus, and ThousandEyes, and the ability to script against their APIs.

• Experience operating RDMA/RoCE lossless fabrics for GPU or HPC workloads, including familiarity with PFC, ECN, and DCQCN tuning.

• Solid hands-on knowledge of BGP, EVPN-VXLAN, IS-IS, OSPF, MPLS, QoS, and TCP/IP in production data center environments.

• Proficiency with Arista (EOS) and Juniper (Junos) platforms in leaf-spine CLOS architectures across multi-vendor environments.

• Comfort operating large device fleets across multi-region environments with on-call responsibility.

• Bachelor's degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.

Bonus Points:

• Experience with NVIDIA/Mellanox networking platforms in GPU cluster environments.

• Familiarity with Kentik or Arbor for traffic analysis and DDoS visibility.

• Exposure to contributing to SLIs and SLOs alongside SRE or product teams.

• Exposure to operating 10K+ device fleets across hyperscale or cloud environments.

Benefits:

• Competitive compensation

• Restricted Stock Units

• Paid time off & paid holidays

• Comprehensive health, dental & vision insurance

• Employer contributions to HSA account

• Paid parental leave

• Paid life insurance, short-term and long-term disability

• Professional development & tuition reimbursement

• Mental health & wellness support

• Commuter benefits (parking & transit)

• Cell phone stipend

• 401(k) Retirement plan with company match up to 4% of salary

• Volunteer time off

Compensation Range:

Compensation will be paid in the range of $165,000 - $200,000 plus Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant’s education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.

Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.