Technology Leader, Platform Architecture, Scalability &...

Role OverviewWe are seeking a senior Technology Leader to own the architecture, scalability, and intelligent automation of our core FinTech platforms. This role is responsible for designing large-scale, cloud-native, distributed systems while leveraging AI-driven automation to improve platform efficiency, reliability, and operational scale.The ideal candidate combines deep expertise in platform architecture and distributed systems with a strong point of view on using AI to automate infrastructure operations, optimize performance, and enable predictive, self-healing platforms. This is a highly technical leadership role with material influence over how the platform scales as the business grows.Key ResponsibilitiesPlatform Architecture & Technical StrategyOwn the end-to-end platform architecture supporting core FinTech products and transaction flowsDefine architectural standards for scalability, performance, resiliency, and system composabilityLead evolution from tightly coupled or monolithic systems toward distributed, service-oriented platformsEstablish clear system boundaries, ownership models, and architectural governanceDefine and execute a multi-year platform roadmap aligned with growth, transaction scale, and product velocityScalability & Distributed SystemsDesign platforms capable of handling high transaction volumes, burst traffic, and sustained throughputGuide horizontal scaling strategies across compute, storage, data, and messaging layersLead architectural decisions around sharding, partitioning, caching, asynchronous processing, and concurrencyContinuously improve latency, throughput, and resource efficiency across the platformEnable multi-region and multi-environment scalability where requiredCloud & Infrastructure ArchitectureArchitect cloud platforms (AWS, Azure, or GCP) optimized for scale, availability, and operational efficiencyDefine reference architectures for containerized workloads, microservices, and distributed runtimesLead Kubernetes and container platform adoption and standardizationMature Infrastructure as Code (Terraform, CloudFormation, etc.) for consistent, scalable environmentsOwn capacity modeling, growth forecasting, and infrastructure lifecycle planningAI-Driven Automation & Intelligent PlatformsApply AI and machine learning techniques to automate platform operations and decision-makingUse AI for:Capacity forecasting and demand predictionAnomaly detection in platform performance and system behaviorAutomated root-cause analysis and incident correlationPredictive scaling and infrastructure optimizationDrive adoption of self-healing platform patterns where systems can respond automatically to failure or degradationEnable data pipelines, feature stores, and runtime environments required to support AI-enabled platform servicesPartner with data and engineering teams to productionize AI capabilities within core platform workflowsPlatform Engineering & Developer EnablementBuild shared platform capabilities that abstract complexity and enable product teams to scale independentlyProvide self-service infrastructure, golden paths, and opinionated platform toolingStandardize CI/CD, runtime environments, observability, and deployment patternsReduce friction and cognitive load for application teams through strong platform designMeasure and improve developer experience as a platform outcomeReliability, Performance & Intelligent OperationsLead SRE practices focused on scalability, automation, and operational maturityDefine and track SLIs/SLOs centered on throughput, latency, availability, and platform healthEstablish advanced observability (metrics, tracing, logging) as inputs to AI-driven insightsLead analysis of scaling failures, performance bottlenecks, and systemic inefficienciesDrive continuous improvement toward predictable, automated, and resilient operationsRequired Qualifications10+ years of experience designing and operating large-scale distributed systems5+ years in senior technical leadership roles (Director, Principal, VP, or equivalent)Deep expertise in platform architecture, cloud-native design, and system scalabilityStrong hands-on experience with AWS, Azure, or GCPProven experience with microservices, event-driven architectures, and distributed data systemsSolid background in Infrastructure as Code and automation-first platform designExperience applying AI/ML concepts to operational or platform use casesPreferred QualificationsExperience with high-volume transaction processing or real-time systemsStrong Kubernetes and container platform experienceExperience with event streaming platforms (Kafka or equivalent)Background modernizing legacy platforms at scaleExperience with AI-assisted operations, AIOps, or intelligent monitoring platformsKey CompetenciesSystems-level architectural thinking with a strong scalability mindsetAbility to blend platform engineering and AI automation into practical solutionsTechnical credibility with senior engineers, architects, and leadershipPragmatic decision-maker who balances ideal architecture with real-world constraintsStrong communicator who can translate technical strategy into business impact30-60-90 Day Success PlanFirst 30 Days - Understand & AssessDevelop deep understanding of current platform architecture and scaling limitsReview system topology, transaction paths, and performance characteristicsIdentify opportunities for automation, AI-driven optimization, and architectural simplificationBuild strong relationships across engineering, data, and product leadershipDays 31-60 - Architect & AutomateDefine target-state platform architecture with explicit scalability patternsPrioritize architectural improvements with the highest scale and automation leverageIntroduce AI-enabled insights into observability, capacity, or incident analysisEstablish platform standards, reference architectures, and design principlesDays 61-90 - Scale & IndustrializeDeliver measurable improvements in throughput, latency, and platform stabilityAdvance automation toward self-service, self-scaling, and self-healing capabilitiesRoll out platform-level AI automation for operations and performance optimizationFinalize a multi-year platform and AI-automation roadmapEstablish a culture of building intelligent systems designed to scale by default

Created: 2026-05-09