Solutions Architect, DevOps

Solutions EngineerSolutions EngineerFull TimeRemoteSeniorTeam 10,001+Since 1993H1B SponsorCompany SiteLinkedIn

Location

Poland

Posted

4 days ago

Salary

zł221.3K - zł507K / year

Seniority

Senior

Job Description

Solutions Architect, DevOps

NVIDIA

• Advise on and help maintain large-scale computational and AI infrastructure, including monitoring, logging, and workload orchestration (Kubernetes and Linux job schedulers). • Provide consultative guidance and perform hands-on troubleshooting across the full stack—from bare metal and operating system, through the software stack, container platform, networking, and storage. • Assess customer environments and recommend optimized, production-ready Kubernetes-based container platforms integrated with enterprise-grade networking and storage solutions. • Serve as a key technical resource: develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams and customer stakeholders. • Support Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches. • Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams. • Act as the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.

Job Requirements

  • BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields
  • 5+ years of professional experience in managing scalable cloud environments and automation engineering roles.
  • Proven understanding of networking fundamentals, data center architectures, and hands-on experience managing HPC/AI clusters, including deployment, optimization and troubleshooting.
  • Demonstrated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver management, CUDA toolkit integration, and GPU workload profiling.
  • Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with GPU-accelerated and HPC environments.
  • Strong familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks.
  • Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and protocols.
  • Proficiency in Python and Bash scripting, configuration management, and Infrastructure-as-Code tools (e.g., Ansible, Terraform).
  • Experience with observability stacks (Grafana, Loki, Prometheus) for monitoring, logging, and building fault-tolerant systems.
  • Strong background in crafting scalable solutions and providing consultative support to customers, including leading architectural reviews and presenting to executive stakeholders.

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