About Intellibus Intellibus designs and engineers platforms trusted by established FinTech and financial-services firms. Our engineering teams build systems that support mission-critical business operations, data-intensive applications, and financial technology platforms. We value engineers who combine strong technical fundamentals with ownership, sound judgment, and the ability to deliver reliable production systems. The Reliability Engineer Role We are hiring a hands-on Reliability Engineer to improve the availability, performance, resilience, and operational stability of enterprise applications and cloud platforms. You will work across cloud infrastructure, application monitoring, incident management, automation, and data platforms to identify reliability risks and deliver measurable improvements. This is an engineering role for someone who can troubleshoot complex issues, automate repetitive operational work, and implement lasting solutions rather than simply respond to alerts. Experience with Microsoft Azure, Python, SQL, and data-intensive applications will be particularly valuable. What You Will Do Reliability & Production Engineering Monitor application health, availability, latency, and system performance. Troubleshoot production incidents, perform root-cause analysis, and implement preventive measures. Improve system resilience through fault analysis, capacity planning, and recovery strategies. Establish and maintain service-level indicators (SLIs), service-level objectives (SLOs), and operational standards. Cloud & Platform Engineering Support and optimize cloud-hosted applications and services on Microsoft Azure. Automate infrastructure and operational tasks using Python and scripting. Improve deployment reliability, configuration management, and release processes. Identify bottlenecks across applications, databases, integrations, and cloud infrastructure. Monitoring & Automation Develop monitoring, alerting, logging, and operational dashboards. Reduce manual intervention through automation and repeatable operational workflows. Participate in incident reviews and translate findings into engineering improvements. Data & AI Platform Reliability Support the reliability and performance of data-intensive applications involving SQL, data modeling, and Microsoft Fabric. Help monitor data pipelines, integration workflows, and data-processing failures. Where applicable, support operational monitoring of AI/LLM-enabled services and their dependencies. What Sets You Apart You should demonstrate several of the following: Hands-on experience supporting production applications or cloud platforms. Ability to troubleshoot complex technical issues and identify root causes independently. Practical experience with Microsoft Azure and Python scripting. Understanding of SQL, databases, data flows, and performance troubleshooting. Ability to automate operational tasks instead of relying on manual processes. Knowledge of monitoring, incident response, capacity planning, and reliability engineering. Taking ownership of issues through resolution and prevention. Clear communication with developers, infrastructure engineers, and business stakeholders. Technology Ecosystem Cloud: Microsoft Azure Programming & Automation: Python, scripting Data: SQL, data modeling, Microsoft Fabric Reliability: Monitoring, alerting, incident management, root-cause analysis, performance optimization Engineering Practices: CI/CD, automation, production support, disaster recovery, service reliability Hiring Process Initial Screening: 15-minute video call with the Recruiting Team. Assessments: One proctored GQ multiple-choice assessment and a SlideWare presentation (under 2 hours). Interview Rounds: Three 30-minute video interviews with the Technical Team, Project Lead, and Executive Team. Offer: Final decision and job offer. If this sounds like the kind of work you want to be doing, apply now. Our team will be in touch within the hour.