Principal Software Engineer - Fleet Management

Location: AMER

Department: AI Infra Technology

About Nscale

Nscale is building a vertically integrated GenAI cloud from sustainable data centers to advanced AI infrastructure and enterprise applications. Our culture values open collaboration, ownership, and excellence.

About the Role

We're hiring a Principal Software Engineer to lead the technical development of our Fleet Manager platform - the workflow automation system that provisions, tests, and remediates GPU nodes and network switches at scale.

As technical lead, you'll own the architecture and delivery of foundational Python-based automation systems that manage the entire lifecycle of our compute infrastructure: device enrolment, burn-in testing, network configuration, GPU health monitoring, and self-healing capabilities. You'll mentor a team of senior engineers, set technical direction, and drive engineering excellence while remaining hands-on with critical systems.

What you'll do

• Lead technical architecture and roadmap for Fleet Manager's workflow automation systems
• Own end-to-end delivery of device provisioning, validation, testing, and remediation workflows at scale
• Design and build workflow orchestration systems for GPU node and network switch lifecycle management
• Establish engineering standards for reliability, observability, and operational excellence across all Fleet Manager services
• Mentor and raise the bar for a team of senior engineers through design reviews, technical leadership, and hands-on collaboration
• Drive architecture decisions balancing automation complexity, reliability, and maintainability
• Integrate with infrastructure tooling: DCIMs, NetBox, OpenStack, bare metal APIs (MAAS, Ironic, IPMI)
• Partner with Infrastructure, Platform, and SRE teams to translate operational needs into robust, scalable automation
• Build production-grade Python systems for hardware lifecycle automation, leveraging AI tools to accelerate delivery

About You

• You have 12-15+ years software engineering experience building and operating production systems, with proven technical leadership in infrastructure automation or workflow tooling
• Strong Python engineering fundamentals with experience leading complex, multi-service distributed systems
• You are driven by building distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement
• Technical expertise: quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems
• Track record of owning technical roadmaps and delivering large-scale automation systems from ambiguous requirements to production
• You use AI tools like Claude or Cursor as a core part of your development workflow - as a fundamental multiplier of what you can build
• Deep understanding of operational excellence: SLOs, monitoring, alerting, incident response, and production reliability
• Strong mentorship skills with ability to develop high-performing engineering teams
• Excellent communication skills to build consensus with stakeholders, both internally and externally

Strong candidates will have

• Experience with workflow orchestration tools like Temporal, Airflow, Prefect, or similar
• Hands-on experience with infrastructure tooling: DCIMs, NetBox, OpenStack, or ERP systems
• Bare metal provisioning and automation: MAAS, Ironic, IPMI, PXE boot, or network automation
• Experience building hardware lifecycle automation: provisioning, validation, testing, or remediation workflows
• GPU infrastructure experience: health monitoring, burn-in testing, or cluster management
• HPC and networking: datacenter topology, high-performance interconnects (InfiniBand, RoCE)
• Deep knowledge of Kubernetes, Infrastructure as Code (Terraform, Pulumi), AWS, and GCP
• Track record of 1+ years leading large-scale, complex projects or technical teams
• Open-source contributions in infrastructure automation or cloud-native tooling