Java Lead

Role SummaryLead the strategy, architecture, delivery, and operational excellence of critical enterprise platforms supporting Payments, Reconciliation, Pricing, and Integration Services. The ideal candidate combines strong technical leadership, platform engineering expertise, and stakeholder management skills with a focus on operational resilience and AI-enabled engineering practices.Key ResponsibilitiesOwn platform roadmap, architecture, and delivery for enterprise payment, pricing, reconciliation, and integration services.Drive the design and operation of scalable, reliable, and auditable microservices, APIs, and event-driven systems.Establish standards for reliability, observability, security, compliance, change management, and release readiness.Partner with Product, Finance, Operations, Merchandising, Architecture, and Engineering teams to prioritize initiatives and align business and technology objectives.Lead modernization efforts, technical direction, staffing transitions, vendor management, and knowledge transfer to reduce dependency on external contractors.Required 10+ years of software engineering, platform engineering, or enterprise application development experience.3+ years in a Technical Lead, Staff Engineer, Engineering Manager, or similar leadership role.Strong expertise in Java/J2EE, springboot, microservices, APIs, event-driven architectures, cloud-native platforms, observability, and production engineering.Experience with financially sensitive transactional systems such as payments, settlements, reconciliation, pricing, or high-volume enterprise platforms.Proven ability to manage complex stakeholder environments and drive cross-functional alignment.Nice to haveImplement AI-assisted engineering practices across design, development, testing, code review, and release management.Leverage agentic workflows for impact analysis, documentation generation, dependency mapping, runbook creation, and incident response support.Drive productivity improvements through automation while maintaining strong governance, security, compliance, and audit controls.Establish measurable outcomes for AI adoption and engineering efficiency without compromising platform integrity.