Senior Platform/Solution Architect

Role Overview

This position centers on converting projected business expansion, user demand, and workload characteristics into concrete infrastructure needs for containerized microservices, hybrid cloud, and data-center deployments. Day to day, the architect builds sizing models, evaluates performance testing outcomes, and guides engineering teams to ensure services remain resilient, responsive, and cost-efficient. The work directly shapes procurement decisions, scaling policies, and long-term platform roadmaps, so every recommendation must balance technical reliability with financial practicality.

Key Responsibilities

• Develop quantitative capacity models for applications and platforms, translating traffic forecasts, transaction volumes, and business growth into CPU, memory, pod, replica, node, cluster, database, storage, and network requirements.
• Lead workload modelling for normal, peak, burst, and exceptional conditions, ensuring infrastructure plans support availability, disaster recovery, and business continuity targets.
• Define resource requests and limits for containerized services, determine horizontal and vertical scaling policies, and calculate node density and cluster headroom for Kubernetes/OpenShift environments.
• Analyse production telemetry—metrics, logs, traces, and APM data—to establish performance baselines, capacity thresholds, and early-warning dashboards that flag impending resource exhaustion.
• Specify and oversee load, stress, endurance, spike, scalability, and capacity validation tests, then use results to confirm or adjust infrastructural sizing assumptions.
• Review existing environments to identify over-provisioning, under-provisioning, bottlenecks, and capacity risks, then recommend targeted optimisation or expansion actions.
• Establish and maintain sizing methodologies, architecture governance, and capacity review processes so new services meet performance, scalability, and resilience standards before production launch.
• Produce and maintain key deliverables such as application capacity models, infrastructure bills of materials, three-to-five-year forecasts, cloud cost/TCO models, and capacity risk assessments.

Requirements & Qualifications

• 10–15+ years of experience in solution architecture, platform architecture, cloud infrastructure, capacity planning, performance engineering, or adjacent disciplines.
• Demonstrated expertise in designing and dimensioning large-scale distributed systems, especially microservices platforms running on Kubernetes or OpenShift.
• Hands-on experience with both cloud and on-premises infrastructure, including container orchestration, database sizing, storage IOPS, network bandwidth, and high-availability design.
• Strong quantitative skills for analysing RPS/TPS, concurrency, response times, CPU and memory consumption, pod densities, scaling thresholds, and infrastructure utilisation.
• Familiarity with observability and monitoring tools such as Prometheus, Grafana, OpenTelemetry, Dynatrace, or AppDynamics, and the ability to turn telemetry into actionable capacity forecasts.
• Proven track record in performance engineering, including designing load tests, interpreting bottlenecks, and validating sizing models using real-world results.
• Experience in transaction-intensive sectors such as telecoms, financial services, or large digital platforms is highly desirable.
• A strong grasp of cost-efficiency principles, including cloud pricing models, reserved capacity, autoscaling, and total cost of ownership analysis.