Service Reliability Engineer

Job Description

Role summary: Reporting to the Lead Service Reliability Engineer, the Service Reliability Engineer is part of an enablement team that provides expertise and support to specialist teams designing, developing and running customer-facing products as well as internal systems. The Service Reliability Engineer will on a day-to-day basis be responsible for the Observability of Creditsafe’s Technology estate and will be involved in the monitoring and escalation of events. A large part of the role will involve improving the monitoring system and processes. This role will involve integrating AI capabilities to reduce noise and improve incident mean time to repair. Role objectives: Ensure our products are ready for life in Production Embed reliability, observability, and supportability as features, across the lifecycle of solution development Help to guide our engineering team’s transformation Raise the bar for engineering quality Deliver higher service availability Improve Creditsafe’s Monitoring Capabilities utilizing AI technologies Personal qualities: Trustworthy and quick thinking Optimistic & Resilient; breed positivity and don’t give up on the “right thing” Leadership & Negotiation; sell not tell, build support and consensus Creativity and High standards; develop imaginative solutions without cutting corners Fully rounded; experience of dev, support, security, ops, architecture and sales As a Service Reliability Engineer, you should have: A track record of troubleshooting and resolving issues in live production environments and implementing strategies to eliminate them Experience in a technical operations support role Demonstratable knowledge of AWS CloudWatch – Creating dashboards, metrics, and log analytics Knowledge of one or more high-level programming languages such as Python, Node, C# and Shell scripting experience. Proactive Monitoring and Alert Validation - Monitor critical infrastructure and services; validate alerts by analyzing logs, performance metrics, and historical data to reduce false positives. Incident Response and Troubleshooting - Perform troubleshooting; escalate unresolved issues to appropriate technical teams; actively participate in incident management and communication. Knowledge of AI/ML frameworks and tools for building operational intelligence solutions and automating repetitive SRE tasks. Continuous Improvement – Improvement of monitoring solutions, reduction of alert noise and implementation of AI technologies: AI/ML experience in operations, including predictive analytics for system health, automated root cause analysis, intelligent alert correlation to reduce noise and false positives, and hands-on experience with AI-powered monitoring solutions for anomaly detection and automated incident response. Strong ability and enthusiasm to learn new technologies in a short time particularly emerging AI/ML technologies in the DevOps, Platform and SRE space. Proficient in container-based environments including Docker and Amazon ECS. Experience of automating infrastructure using “as code” tooling. Strong OS skills, Windows and Linux. Understanding of relational and NoSQL databases. Experience in a hybrid cloud-based infrastructure. Understanding of infrastructure services including DNS, DHCP, LDAP, virtualization, server monitoring, cloud services (Azure and AWS). Knowledge of continuous integration and continuous delivery, testing methodologies, TDD and agile development methodologies Experience using CI/CD technologies such as Terraform and Azure Dev Ops Pipel Show more Show less