You’d be a top applicant - Senior Solutions Architect, AI Factory Observability and Visualization - NVIS
Your profile and resume appear to match several of the job’s qualifications well. Based on my review of your information and similar applications on LinkedIn, you could have a higher chance of hearing back if you apply.

 

Matches 5 of the 8 required qualifications:

✓ Bachelor's degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field.

✓ 6+ years of experience managing Linux-based systems in HPC, distributed systems, or large AI/ML settings.

✓ Proficiency with Python and Shell/Bash for scripting, automation, and tooling.

✓ Practical experience working with observability systems (e.g., Prometheus, Grafana, Loki, or similar), including building custom exporters or collectors, setting up alerts, and handling metric cardinality and retention on a large scale.

✓ Experience transforming metrics, logs, and traces into clear, actionable insight for complex distributed environments.

? Hands-on experience with the architecture of multi-GPU and/or multi-node clusters, including networking and interconnects. (No specific mention of multi-GPU or multi-node cluster architecture)

? Solid grasp of how HPC and AI factory systems fit together end to end, from network fabric through compute. (No specific mention of HPC and AI factory systems)

? Familiarity with GPU and fabric telemetry (e.g., DCGM, NVLink, InfiniBand/Ethernet fabric counters) and using it to diagnose performance regressions. (No specific mention of GPU and fabric telemetry)

 

Matches 0 of the 3 additional qualifications:

? Experience with AI factory or large-scale AI infrastructure build, deployment, or operations. (No specific mention of AI factory or large-scale AI infrastructure)

? Background in HPC systems engineering, SRE, or systems analysis for GPU-accelerated environments. (No specific mention of HPC systems engineering or GPU-accelerated environments)

? Experience building automation and data pipelines that feed dashboards and reporting at scale. (No specific mention of building automation and data pipelines)

 

There are qualifications that will likely be evaluated in the application or interview:

• Strong communication skills and the ability to work effectively with cross-functional teams.

• Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions.