SRE: AI‑Driven Reliability & Observability

Socket.dev; Minnesota; On-site; USD 71,000 - 131,000; Full time

Benefits offered by this job

Hybrid Work Model

Career Development

Mental Health Days

401k Plan

Job summary

Thomson Reuters is fortifying its Site Reliability Engineering capability to build, operate, and improve reliable production services. You will work with observability platforms, automation, and AI-enabled tools to improve the quality and availability of context used during incidents.

This hands-on role emphasizes learning across platforms, improving runbooks and telemetry, and collaborating with Product Engineering and platform teams to reduce toil and enhance reliability.

Qualifications

• 3+ years in Site Reliability Engineering, DevOps, cloud infrastructure, or related field.
• Experience with production telemetry (logs, metrics, traces, dashboards).
• Experience troubleshooting production issues and incident response.
• Experience with scripting or programming (Python, Bash, JavaScript, Go, etc.).
• Ability to document operational processes and runbooks clearly.
• Familiarity with AI-enabled coding or incident-management tools.

Responsibilities

• Maintain SRE tooling: dashboards, alerts, runbooks, and telemetry baselines.
• Investigate service health using logs, metrics, traces, and alerts.
• Participate in incident response and post-incident reviews.
• Execute runbooks within change-management processes.
• Document facts, observations, and actions during incidents and handoffs.
• Contribute to automation and deployment telemetry enhancements.
• Review and validate AI-generated operational artifacts.

Skills

Site Reliability Eng

Cloud infrastructure

Observability & monitoring

Incident response

Scripting (Python, Bash)

Communication

Tools

Datadog

Dynatrace

New Relic

Grafana

Prometheus

Job description

Thomson Reuters is fortifying its Site Reliability Engineering capability to build, operate, and improve reliable production services. You will work with observability platforms, automation, and AI-enabled tools to improve the quality and availability of context used during incidents.

This hands-on role emphasizes learning across platforms, improving runbooks and telemetry, and collaborating with Product Engineering and platform teams to reduce toil and enhance reliability.