Senior Software Engineer - DevOps, SRE, AIOps
$50,000–$125,000 year
On-siteGalway, Connacht, Ireland
Job Summary
Drive adoption of CI/CD pipelines, Infrastructure as Code, and GitOps practices to standardize development and deployment workflows. Lead the evolution from traditional monitoring to AI-driven operations by integrating machine learning models for predictive monitoring, anomaly detection, and automated root cause analysis. Architect scalable observability frameworks covering metrics, logs, and traces to enable real-time insights across microservices and cloud-native architectures. Establish enterprise-wide SRE practices including SLIs, SLOs, error budgets, and reliability governance while building self-healing systems to reduce Mean Time to Resolution. Mentor engineers and influence architecture decisions to embed reliability and automation into the software delivery lifecycle.
Required Qualifications
- 3+ years of experience in software engineering, SRE, or production engineering in large-scale distributed systems
- Hands-on experience with Observability tools such as AppDynamics, Grafana, Prometheus, Datadog, OpenTelemetry, or similar
- Experience with AIOps or intelligent monitoring platforms, including anomaly detection and event correlation
- Strong expertise in cloud platforms (AWS, Azure, or GCP), cloud-native architectures (Kubernetes, containers, microservices), and CI/CD pipelines (GitHub Actions, Jenkins)
- Proficiency in at least one programming language (e.g., Python, Java, Go)
- Strong understanding of distributed systems, resiliency patterns, and fault tolerance
- Experience implementing incident management, on-call processes, and root cause analysis
- Hands-on expertise with Infrastructure as Code (Terraform, ARM, CloudFormation) and CI/CD pipelines
- Experience using GenAI/Automation tools and frameworks such as OpenAI, CoPilot, Gemini, Claude, MCP etc
- Proven ability to design scalable, reliable, and observable systems
- Bachelor's degree or equivalent work experience in Computer Science, Engineering, or related discipline
Desired Qualifications
- Experience designing and implementing AIOps platforms or predictive reliability systems at scale
- Strong knowledge of machine learning applications in IT operations (e.g., anomaly detection, forecasting, clustering)
- Experience defining and managing SLIs/SLOs and error budgets at scale
- Experience with OpenTelemetry and modern observability standards
- Familiarity with chaos engineering, resilience testing, and fault injection frameworks
- Exposure to GenAI-driven operations or AI-assisted troubleshooting tools
- Experience in healthcare, finance, enterprise SaaS, or highly regulated industries
- Demonstrated leadership in driving cross-functional initiatives and influencing senior stakeholders
- Contributions to open-source projects in SRE, observability, or AIOps domains
- Certifications in AIOps, SRE, OpenTelemetry, cloud platforms, or DevOps
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