Cloud Platform System Engineer

Job description

**Job Title:** Cloud Platform System Engineer **Key Skills:**Python, Containerization, Linux Administration, CI/CD Pipelines, Cloud Monitoring & Observability, Performance **Location:**Brazil **Mode:** Remote We at **Coforge** are seeking a highly skilled and experienced **Cloud Platform System Engineer** to join our team. This role focuses on performance assessment, system limits evaluation, and KPI-driven analysis for a Private Cloud Platform solution designed for distributed Edge computing. You will be part of a talented team responsible for delivering a robust private cloud platform that supports containerized applications, virtual machines, and bare metal nodes. **Key Responsibilities:** - Define and maintain Key Performance Indicators (KPIs) that characterize the platform's performance boundaries and system limits, including scalability ceilings, resource saturation thresholds, latency budgets, and throughput baselines. - Track KPI trends across builds and releases, identifying performance regressions, drift, or degradation patterns early in the development cycle. - Execute performance assessments as part of pre-release validation, providing data-driven evidence for release readiness decisions. - Design and develop test workloads, synthetic applications, and stress scenarios to stimulate the system under controlled conditions and expose performance characteristics. - Develop and maintain tools, frameworks, and automated pipelines for continuous performance measurement, data collection, and KPI reporting. - Execute and analyze performance experiments (load, soak, spike, scalability, endurance) to identify system limits and regression points. - Analyze performance-related issues reported from production to identify gaps in current KPIs, test workloads, or measurement coverage, and incorporate findings into the assessment process for subsequent releases. - Support reproducibility of performance results by documenting environments, configurations, workloads, and measurement methodologies. - Troubleshoot performance anomalies and regressions by correlating system metrics, logs, traces, and resource utilization data across distributed components. - Collaborate with development and test teams to provide performance insights that inform architecture decisions, capacity planning, and release readiness. - Contribute to a highly available, carrier-grade private cloud platform aimed to be at the core of 5G and distributed Edge deployments worldwide. **Required Skills & Qualifications:** - Proficiency in Python for developing automation scripts, tools, or pipelines for performance data collection, analysis, or reporting. - Strong analytical, troubleshooting, and attention to detail skills, with a data-driven and methodical approach to performance investigation. - Strong Linux familiarity, including terminal usage and understanding of OS internals (process scheduling, memory management, file systems, I/O subsystems, cgroups, namespaces). - Experience with Linux performance observability tools (e.g., perf, top/htop, vmstat, iostat, sar, dstat, pidstat, strace, bpftrace). - Experience collecting, correlating, and interpreting system metrics (CPU, memory, disk I/O, network throughput/latency) in distributed architectures. - Strong understanding of computer networking at the transport (TCP/UDP) and network (IP) layers, with the ability to assess network performance characteristics (bandwidth, latency, packet loss, jitter). - Experience installing, deploying, and configuring systems and applications on Linux-based hosts. - Able to communicate in English at a minimum according to the parameters of level B2 for understanding, speaking, and writing of the CEFR matrix. **Preferred Skills:** - Experience defining KPIs for infrastructure or platform systems. - Experience with Linux performance testing frameworks or load generation tools (e.g., fio, iperf, qperf, cyclictest). - Experience building CI/CD pipelines that integrate performance benchmarking (e.g., Jenkins, GitLab CI, GitHub Actions). - Kubernetes cluster administration and understanding of K8s performance dimensions. - OpenStack administration and performance considerations. - Experience with monitoring and observability stacks (e.g., Prometheus, Grafana, ELK/OpenSearch, collectd, telegraf). - Understanding of Docker/Containers and their performance implications. - Knowledge of cloud platform concepts and capacity planning. - Experience with large-scale systems monitoring and alerting. **Posted On:** 21-08-2026 **At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.**