Site Reliability Engineer

Job summary

Leads the design, implementation, and operation of enterprise observability platforms across applications, infrastructure, and AI-enabled environments. Establishes standards for logging, metrics, distributed tracing, monitoring, alerting, and self-healing, while integrating observability with CI/CD pipelines, CMDB, and ServiceNow. The role also defines end-to-end AI workflow telemetry and evaluation to improve reliability, operational visibility, and incident resolution.

Qualifications

• Bachelor’s degree in computer science or engineering, or equivalent combination of education and experience
• 1–3 years of site reliability engineering, DevOps, or platform engineering experience
• Hands-on experience building and operating enterprise observability platforms
• Expertise with Datadog and SolarWinds
• Experience designing observability for cloud, hybrid, and on-premises environments, including Azure, Kubernetes, and virtual machines
• Knowledge of logging platforms, application performance monitoring, distributed tracing, and infrastructure monitoring
• Knowledge of generative AI and LLM architectures, including RAG, vector databases, agents, and tool integrations
• Experience with OpenTelemetry or comparable instrumentation standards
• Understanding of AI telemetry, quality evaluation, drift detection, guardrails, and privacy requirements
• Proficiency in Python or PowerShell and experience integrating observability into CI/CD pipelines
• Experience with infrastructure-as-code, configuration management, Docker, and Kubernetes
• Strong troubleshooting, incident management, documentation, and cross-functional leadership skills

Responsibilities

• Lead enterprise observability standards for logging, metrics, tracing, and alerting
• Own the observability platform strategy and roadmap, including Datadog and SolarWinds
• Define instrumentation standards for applications, APIs, and infrastructure
• Integrate observability into CI/CD pipelines and deployment requirements
• Develop automated monitoring, alerting, and self-healing patterns
• Create reusable observability frameworks, libraries, and deployment templates
• Establish monitoring-as-code, alerting-as-code, and dashboard-as-code standards
• Define SLIs, SLOs, and error budgets with product and engineering teams
• Provide monitoring coverage across cloud, on-premises, containerized, and hybrid environments
• Implement distributed tracing and log correlation for end-to-end transaction visibility
• Define tracing, evaluation, and telemetry governance for AI-enabled and agentic workflows
• Lead complex reliability investigations, root cause analysis, and post-incident improvements
• Integrate observability platforms with ServiceNow, CMDB, and service mapping
• Improve alert quality, deployment reliability, capacity planning, and operational readiness
• Develop engineering training and enablement materials for observability practices

Skills

Degrees

Relocation