Senior SRE — AI Platform Reliability & Automation

nscaleoperationsukltd; Houston (TX); On-site; USD 130,000 - 200,000; Full time

Benefits offered by this job

Competitive base plus equity

Real scope early

Flexible work style

Job summary

Nscale is seeking a career-level SRE to own automated tooling and reliable systems for AI workloads. You will sit in rotation, reduce toil, and push for quieter, more stable production services across Linux and networking.

This role emphasizes ownership, fast iteration, and measurable reliability improvements. You’ll partner with Engineering and Infrastructure to raise the reliability bar while delivering scalable, efficient platforms for AI-native workloads.

Qualifications

• 3–6 years in SRE or systems engineering with production exposure.
• Strong programming skills (Python/Go) and automation bias.
• Solid Linux, networking, and distributed systems knowledge.
• Proven incident RCA and postmortem experience.
• Fluency in monitoring and observability.

Responsibilities

• Build and own automation and tooling to keep the platform running.
• Define and maintain SLOs, SLIs, and dashboards.
• Lead incidents, perform root cause analysis, and drive post-incident reviews.
• Troubleshoot performance and reliability across Linux, networks, and distributed services.
• Collaborate with Engineering, Networking, and Infrastructure to raise reliability.
• Improve availability, scalability, and efficiency through code.

Skills

SRE experience

Python/Go programming

Linux networking

Incident response

Observability

Automation mindset

Tools

Kubernetes

Bare-metal / virtualization

Job description

Nscale is seeking a career-level SRE to own automated tooling and reliable systems for AI workloads. You will sit in rotation, reduce toil, and push for quieter, more stable production services across Linux and networking.

This role emphasizes ownership, fast iteration, and measurable reliability improvements. You’ll partner with Engineering and Infrastructure to raise the reliability bar while delivering scalable, efficient platforms for AI-native workloads.