# Sr Platform/Solution Architect Job Tezza Business Solutions, Nairobi, Kenya Canonical URL: https://primejobalerts.com/jobs/sr-platformsolution-architect-job-tezza-business-solutions-nairobi-kenya Company: Tezza Business Solutions, Nairobi, Kenya Category: Banking & Financial Services Location: Kenya Work type: Full-time Work arrangement: On-site Published: 2026-08-18 Expires: 2026-10-02 ## Job Description Role Purpose  - The Senior Platform/Solution Architect – Capacity Planning, Performance & Cloud Infrastructure Architecture is responsible for translating business demand, application traffic and workload characteristics into quantifiable infrastructure requirements across microservices, Kubernetes/OpenShift, cloud and on-premises environments. The role provides the technical capability to determine CPU, memory, pod/replica, node, cluster, database, storage and network requirements while ensuring performance, scalability, resilience, availability and cost efficiency.  ### Core Responsibilities - Lead capacity planning and infrastructure dimensioning for applications, platforms and microservices-based services.  - Translate business growth, transaction volumes and traffic forecasts into infrastructure capacity requirements.  - Develop quantitative workload models covering normal, peak, burst and exceptional traffic conditions.  - Determine appropriate CPU, memory, pod/replica, node and cluster requirements for application services.  - Develop capacity forecasts and infrastructure roadmaps covering short-, medium- and long-term demand.  - Ensure capacity plans support availability, resilience, disaster recovery and business continuity requirements.  - Provide architecture and capacity recommendations for both cloud and on-premises environments.  - Review existing environments to identify over-provisioning, under-provisioning, bottlenecks and capacity risks.  Microservices Capacity Planning & Dimensioning  - Assess resource consumption and performance characteristics of individual microservices.  - Determine minimum, normal and maximum pod/replica requirements based on workload and service-level objectives.  - Define CPU and memory requests and limits for containers.  - Assess horizontal and vertical scaling requirements and define appropriate scaling policies.  - Determine node density, resource utilisation and cluster capacity requirements.  - Account for service-to-service communication, platform overhead and infrastructure reserve capacity.  - Establish repeatable sizing methodologies for new applications and services.  - Validate sizing assumptions through performance and capacity testing.  ​​​​​​​Capacity Planning Parameters & Metrics  - Define and maintain standard parameters for application and infrastructure capacity planning.  - Analyse requests per second (RPS), transactions per second (TPS), concurrent users, sessions and transaction volumes.  - Analyse average, peak and burst traffic and associated growth patterns.  - Assess CPU utilisation, CPU consumption per transaction, memory utilisation, memory peaks and application heap requirements.  - Assess pod counts, replica requirements, scaling thresholds and scaling response times.  - Determine node CPU, node memory and allocatable cluster capacity.  - Assess database TPS, connections, CPU, memory, IOPS and throughput.  - Assess storage capacity, IOPS, throughput and growth.  - Assess network bandwidth, latency and packet rates.  - Factor in high availability, N+1/N+2 resilience, disaster recovery, growth headroom and operational reserve.  ​​​​​​​Performance Engineering  - Lead performance engineering and capacity validation for critical applications and platforms.  - Define and oversee load, stress, endurance, spike, scalability and capacity testing.  - Analyse throughput, response time, latency, concurrency and resource utilisation.  - Identify application, platform, database, storage and network bottlenecks.  - Establish performance baselines and capacity thresholds.  - Use performance test results to validate CPU, memory, pod, node and cluster sizing.  - Work with engineering teams to optimise resource consumption and application performance.  Observability & Data-Driven Capacity Planning  - Use production telemetry and historical performance data to develop evidence-based capacity models.  - Leverage metrics, logs, traces and APM data to understand workload behaviour.  - Use monitoring and observability platforms such as Prometheus, Grafana, OpenTelemetry, Dynatrace, AppDynamics or equivalent tools.  - Correlate traffic, application performance, pod utilisation, infrastructure consumption and database performance.  - Establish capacity thresholds, early-warning indicators and capacity risk dashboards.  - Use trend analysis and forecasting to identify future infrastructure requirements before capacity constraints occur.  Architecture Governance & Standards  - Establish standard capacity planning and dimensioning methodologies across the organisation.  - Define architecture principles, sizing standards, resource profiles and capacity governance processes.  - Review and approve application capacity models and infrastructure sizing proposals.  - Ensure new services meet defined scalability, availability, performance and capacity requirements before production deployment.  - Establish governance for capacity reviews following major releases, traffic changes or architectural changes.  - Maintain architecture documentation, capacity assumptions, sizing models and decision records.  ​​​​​​​Key Deliverables  - Application Capacity Model  - Microservices Dimensioning Model  - CPU & Memory Sizing Model  - Pod/Replica Sizing Model  - Kubernetes/OpenShift Cluster Sizing  - Database Capacity Model  - Storage & IOPS Capacity Model  - Network Capacity Model  - Cloud Infrastructure Sizing  - On-Premises Infrastructure Sizing  - Three- to Five-Year Capacity Forecast  - Peak/Event Capacity Plan  - Performance Test Strategy and Capacity Validation Report  - Capacity and Performance Dashboard  - Infrastructure Bill of Materials (BoM)  - Cloud Cost/TCO Model  - Capacity Headroom and Risk Assessment  ​​​​​​​Experience & Professional Profile  - Typically 10–15+ years of experience across solution architecture, platform architecture, cloud infrastructure, capacity planning, performance engineering or related disciplines.  - Proven experience designing and dimensioning large-scale distributed systems and microservices platforms.  - Strong experience with Kubernetes/OpenShift and containerised application environments.  - Hands-on experience with cloud and on-premises infrastructure architecture.  - Demonstrable experience in capacity planning, workload modelling, performance engineering and infrastructure forecasting.  - Experience with large-scale, high-availability, transaction-intensive environments is highly desirable.  - Experience in telecoms, financial services, digital platforms or other high-volume technology environments is advantageous.  ### How to Apply Click here to apply ## Apply Use the canonical Prime Job Alerts page for full application instructions and source verification.