Production Engineer

• Design, build, and evolve highly available cloud infrastructure platforms with a focus on scalability, resilience, and reliability
• Lead improvements across production systems, including performance, availability, and incident response
• Drive and standardize Infrastructure as Code (IaC) practices to improve consistency and reduce operational overhead
• Design and optimize CI/CD pipelines to support fast, secure, and reliable software delivery at scale
• Partner with development teams to improve system reliability, observability, and cloud-native design patterns
• Define and implement monitoring, alerting, and observability strategies across distributed systems
• Lead incident response efforts, including root cause analysis and long-term remediation strategies
• Identify and eliminate operational toil through automation and system improvements
• Mentor engineers and contribute to raising the bar for production engineering practices

Senior Staff Production Engineer – Cloud Platform, Reliability, Machine Identity Security

• Own compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU and TPU in production — across Kubernetes-orchestrated workloads and bare metal, at scale.
• Turn repair into a pipeline, not a procedure. Build and own the automation that takes a compute failure from detection through triage, parts management, and return to service. No one-off scripts, no heroics.
• Design and expand the XPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU and TPU generation. You define what "good" looks like before hardware goes into production.
• Own Redfish and BMC tooling. Firmware-level telemetry, log collection at fleet scale, and the low-level access layer that repair automation and health tooling depend on.
• Own end-to-end reliability, scalability, and operation of the compute fleet at scale. Fluidstack is building one of the largest XPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.

Production Engineer, Compute

• Design, deploy, and manage hybrid and cloud infrastructures (OCI, AWS, Azure, on-prem) to support production and enterprise systems
• Implement infrastructure-as-code (IaC) using Terraform or CloudFormation to ensure repeatable, secure, and automated deployments
• Develop and maintain CI/CD-ready environments that support rapid build, test, and release cycles for engineering teams
• Partner with network and security teams to implement resilient, compliant architectures
• Serve as technical lead for production systems, ensuring stability, performance, and scalability
• Establish monitoring, logging, and alerting frameworks to improve visibility and reduce mean time to detection (MTTD) and resolution (MTTR)
• Participate in incident response, root cause analysis, and reliability improvement efforts
• Collaborate with Engineering and SRE teams to define SLIs, SLOs, and performance metrics for critical services
• Develop and enhance deployment pipelines (e.g., Jenkins, GitLab, ArgoCD) to automate software delivery and environment provisioning
• Embed security, compliance, and testing gates into CI/CD workflows
• Implement configuration management and orchestration tools such as Ansible, Chef, or Puppet to manage infrastructure at scale
• Drive efficiency through self-healing systems, auto-scaling, and infrastructure automation
• Lead day-to-day production operations activities, mentoring junior engineers on cloud and reliability best practices
• Act as a technical bridge between Infrastructure, Security, and Application Engineering teams
• Contribute to capacity planning, cost optimization, and production readiness reviews
• Maintain documentation, runbooks, and standard operating procedures for production systems

Lead Cloud Engineering, Production Operations Engineer

• Set up Server/Network/software Configuration.
• Write customized automation scripts to increase system efficiency
• Manage and monitor all installed systems and infrastructure
• Install, configure, test, and maintain operating systems, application software and system management tools
• Proactively ensure the highest levels of systems and infrastructure availability
• Monitor and benchmark test application performance for potential bottlenecks, identify possible solutions
• Draft and maintain technical documentations including drawing/diagram
• Provide on-site software deployment/customer acceptance verification test

• You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads.
• This includes working on custom software related to GPU asset provisioning, configuration, and lifecycle management across cloud providers.
• Implementing monitoring and health management capabilities that enable industry leading reliability, availability, and scalability of GPU assets.
• You will be harnessing multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
• Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance.
• Evaluating system failures and improving services based on a well-defined incident management process.

Senior Production Engineer – DGX Cloud

• Devise and champion a long-term infrastructure strategy
• Manage and grow a world-class team of Production Support Engineers
• Lead the transition to a multi-region and multi-substrate deployment model
• Oversee the maintenance of legacy environments and bespoke customer deployments
• Ensure our infrastructure meets strict regulatory and data-residency requirements
• Define and hold the team accountable to SLIs, SLOs, and error budgets
• Collaborate with Product, Engineering, and Security leadership
• Build and ship high-quality, production-grade software using modern engineering practices
• Contribute to building and maintaining the shared system context
• Evaluate code (Human or AI-generated) for correctness, quality, security, and performance

Director of Production Support Engineering

• Own the reliability roadmap for major product areas.
• Partner with PMTS-level engineers to refine infrastructure strategy.
• Maintain and evolve automated environments.
• Support scaling of AI/ML infrastructure.
• Lead the hardening of observability stack.
• Deep-dive into SQL optimization, API latency, and cross-service communication.
• Contribute to building and maintaining shared system context.

Production Support Engineer

• Design and implement highly available, scalable infrastructure across AWS, Azure, GCP, and bare-metal environments
• Drive an "automation-first" culture by writing code (Python/Go) to eliminate manual toil and build self-healing systems
• Implement and maintain sophisticated observability (Prometheus, Grafana, OpenTelemetry), define SLIs/SLOs, and establish error budgets
• Act as a lead Incident Commander (TDO on-call), develop response playbooks, and conduct deep-dive post-incident analyses
• Partner with Engineering and partner teams to conduct operability reviews

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