HPC Data Center Production Engineer
P2P, New York, NY, United States
HPC Data Center Production Engineer
Location: Chicago or New York (On-site 5 days/week)
What You’ll Do
Hardware Onboarding Automation
Design, develop, and maintain automation to onboard new hardware devices into Jump’s HPC data centers, including servers, network switches, rack PDUs, CDUs, and environmental sensors.
Build end-to-end provisioning workflows that take hardware from racked-and-cabled through discovery, configuration, validation, and production-ready state with minimal manual intervention.
Extend and adapt onboarding automation as new hardware platforms and device types are introduced.
Data Center Tooling Development
Develop tools for power and cooling capacity planning enabling the operations and planning teams to model current utilization, forecast growth, and identify constraints before they become problems.
Build outage simulation tooling to model the impact of power, cooling, or network failures across HPC facilities and validate redundancy/failover configurations.
Develop and maintain operational tooling that supports day-to-day data center workflows such as hardware lifecycle tracking, data center inventory/spares, change management, and diagnostics.
Monitoring & Metrics Integration
Build and maintain monitoring integrations for HPC data center infrastructure—pulling telemetry from servers, switches, PDUs, CDUs, environmental sensors, and facility systems into centralized observability platforms.
Integrate metrics feeds from colocation and data center providers into Jump’s monitoring stack, normalizing data for alerting and capacity reporting.
Work with the Operations Lead to implement the monitoring and alerting strategy, translating requirements into deployed, production-grade instrumentation.
Cross-Team Collaboration
Work very closely with the HPC Planning, Engineering, and Operations leads to understand tooling and monitoring needs and bring their vision to fruition.
Partner with HPC Engineering on integration points between data center automation and compute/storage
etwork provisioning systems.
Translate operational pain points and manual processes into automated, maintainable solutions.
Systems Maintenance & Reliability
Own the reliability and lifecycle of all systems and tools you develop—monitor for failures, respond to issues, and iterate based on operational feedback.
Maintain comprehensive documentation for all tooling, automation workflows, and integrations.
Participate in large, coordinated maintenance operations, including during evenings and weekends.
AI-Driven Development
Use AI tools daily across all aspects of the role: writing and reviewing code, analyzing data, debugging, generating documentation, and accelerating development velocity.
Identify opportunities to apply AI to data center operations problems—anomaly detection, predictive capacity planning, intelligent alerting, and beyond.
Additional duties as assigned or needed.
Qualifications & Skills
5+ years of professional experience in production engineering, infrastructure automation, or site reliability engineering, preferably in HPC or large-scale data center environments.
Proven track record of building and shipping production automation and tooling—not just scripts, but maintained, reliable systems.
Experience automating hardware provisioning and lifecycle management (servers, network devices, power/cooling infrastructure).
Strong understanding of data center infrastructure: power distribution, cooling systems (air and liquid), environmental monitoring, and structured cabling.
Experience integrating with hardware management interfaces (IPMI/BMC/Redfish, SNMP, vendor APIs) for discovery, configuration, and telemetry collection.
Demonstrates a high level of energy, results driven, and able to work under pressure with tight deadlines.
High proficiency in Golang and at least one additional language (e.g., Python). You will write a lot of code in this role.
Strong Linux systems knowledge—you should live in Linux. Proficient with system administration, networking, storage, process management, log analysis, and troubleshooting at the OS level.
Experience with Grafana for building dashboards, alerting, and visualization of infrastructure metrics. Experience with Prometheus, InfluxDB, or similar observability platforms and building custom integrations/exporters.
Experience with configuration management and infrastructure-as-code tools (SaltStack, Ansible, Terraform, or similar).
Solid understanding of networking concepts: L2/L3 protocols, VLANs, BGP, SNMP, and switch/router configuration (Arista, Cisco).
Experience with APIs and data integration—consuming vendor APIs, normalizing heterogeneous data sources, building data pipelines for metrics and reporting.
Experience with ClickHouse and MySQL—writing queries, designing schemas, and building tooling that reads from and writes to these databases.
Experience with GitHub for version control, code review, CI/CD workflows, and collaborative development.
Demonstrated heavy use of AI tools (e.g., LLM-based coding assistants, AI-driven analytics) in a professional setting. You should already be using AI daily and be eager to push its application further.
A compulsion to perform root cause analysis.
Excellent written and verbal communication skills with the ability to work across a global engineering team.
Extremely high personal standards for work quality.
Reliable and predictable availability, including ability to work evenings and weekends as required.
Bachelor’s degree preferred.
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Location: Chicago or New York (On-site 5 days/week)
What You’ll Do
Hardware Onboarding Automation
Design, develop, and maintain automation to onboard new hardware devices into Jump’s HPC data centers, including servers, network switches, rack PDUs, CDUs, and environmental sensors.
Build end-to-end provisioning workflows that take hardware from racked-and-cabled through discovery, configuration, validation, and production-ready state with minimal manual intervention.
Extend and adapt onboarding automation as new hardware platforms and device types are introduced.
Data Center Tooling Development
Develop tools for power and cooling capacity planning enabling the operations and planning teams to model current utilization, forecast growth, and identify constraints before they become problems.
Build outage simulation tooling to model the impact of power, cooling, or network failures across HPC facilities and validate redundancy/failover configurations.
Develop and maintain operational tooling that supports day-to-day data center workflows such as hardware lifecycle tracking, data center inventory/spares, change management, and diagnostics.
Monitoring & Metrics Integration
Build and maintain monitoring integrations for HPC data center infrastructure—pulling telemetry from servers, switches, PDUs, CDUs, environmental sensors, and facility systems into centralized observability platforms.
Integrate metrics feeds from colocation and data center providers into Jump’s monitoring stack, normalizing data for alerting and capacity reporting.
Work with the Operations Lead to implement the monitoring and alerting strategy, translating requirements into deployed, production-grade instrumentation.
Cross-Team Collaboration
Work very closely with the HPC Planning, Engineering, and Operations leads to understand tooling and monitoring needs and bring their vision to fruition.
Partner with HPC Engineering on integration points between data center automation and compute/storage
etwork provisioning systems.
Translate operational pain points and manual processes into automated, maintainable solutions.
Systems Maintenance & Reliability
Own the reliability and lifecycle of all systems and tools you develop—monitor for failures, respond to issues, and iterate based on operational feedback.
Maintain comprehensive documentation for all tooling, automation workflows, and integrations.
Participate in large, coordinated maintenance operations, including during evenings and weekends.
AI-Driven Development
Use AI tools daily across all aspects of the role: writing and reviewing code, analyzing data, debugging, generating documentation, and accelerating development velocity.
Identify opportunities to apply AI to data center operations problems—anomaly detection, predictive capacity planning, intelligent alerting, and beyond.
Additional duties as assigned or needed.
Qualifications & Skills
5+ years of professional experience in production engineering, infrastructure automation, or site reliability engineering, preferably in HPC or large-scale data center environments.
Proven track record of building and shipping production automation and tooling—not just scripts, but maintained, reliable systems.
Experience automating hardware provisioning and lifecycle management (servers, network devices, power/cooling infrastructure).
Strong understanding of data center infrastructure: power distribution, cooling systems (air and liquid), environmental monitoring, and structured cabling.
Experience integrating with hardware management interfaces (IPMI/BMC/Redfish, SNMP, vendor APIs) for discovery, configuration, and telemetry collection.
Demonstrates a high level of energy, results driven, and able to work under pressure with tight deadlines.
High proficiency in Golang and at least one additional language (e.g., Python). You will write a lot of code in this role.
Strong Linux systems knowledge—you should live in Linux. Proficient with system administration, networking, storage, process management, log analysis, and troubleshooting at the OS level.
Experience with Grafana for building dashboards, alerting, and visualization of infrastructure metrics. Experience with Prometheus, InfluxDB, or similar observability platforms and building custom integrations/exporters.
Experience with configuration management and infrastructure-as-code tools (SaltStack, Ansible, Terraform, or similar).
Solid understanding of networking concepts: L2/L3 protocols, VLANs, BGP, SNMP, and switch/router configuration (Arista, Cisco).
Experience with APIs and data integration—consuming vendor APIs, normalizing heterogeneous data sources, building data pipelines for metrics and reporting.
Experience with ClickHouse and MySQL—writing queries, designing schemas, and building tooling that reads from and writes to these databases.
Experience with GitHub for version control, code review, CI/CD workflows, and collaborative development.
Demonstrated heavy use of AI tools (e.g., LLM-based coding assistants, AI-driven analytics) in a professional setting. You should already be using AI daily and be eager to push its application further.
A compulsion to perform root cause analysis.
Excellent written and verbal communication skills with the ability to work across a global engineering team.
Extremely high personal standards for work quality.
Reliable and predictable availability, including ability to work evenings and weekends as required.
Bachelor’s degree preferred.
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