Lead Software Engineer -Java Backend, Kafka- Payment Technology

Lead Software Engineer -Java Backend, Kafka- Payment Technology

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

 

Job responsibilities

 

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• System design & resiliency (payments-grade): Produce HLD/LLD and implement resilient architectures (timeouts, retries, circuit breakers, bulkheads, backpressure) with failure-mode thinking, deterministic recovery, and strong operational readiness

 

Required qualifications, capabilities, and skills

 

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Payments domain expertise (hands-on): Deep experience building and operating ACH, wires, and instant payments systems across initiation, validation, orchestration/routing, clearing/settlement, returns/recalls/amends, and reconciliation—owning outcomes without formal people management
• Rail-specific processing knowledge (ACH): Strong understanding of batch-oriented processing, cutoffs/windows, file/batch validation, exception flows (returns/NOC-style corrections), and reconciliation patterns; design for reruns, resumability, and controlled reprocessing
• Java/Spring depth (still coding): Expert-level Java (8/11/17+) and Spring Boot/Spring ecosystem; performance tuning (JVM, GC, concurrency), transaction design, and production readiness (health/readiness, config profiles, Actuator, safe feature flags)
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

 

• API contract ownership: Own REST/event contracts for payment initiation, status/tracking, callbacks/webhooks, and recall/amend requests; enforce versioning/backward compatibility, consistent error models/reason codes, and consumer-driven contract testing
• Quality & testing for critical flows: Define and implement testing strategy: golden message vectors, simulators/mocks for rail participants, integration/contract tests, performance tests around cutoffs/spikes, and resiliency/chaos testing; drive root-cause fixes
• Observability & operations: Build full traceability (correlation IDs across services), structured logs/metrics/tracing, meaningful alerts/dashboards (latency, acceptance/reject/return rates, queue depth, settlement/recon breaks); lead incident response and post-incident improvements

Experience Level

Senior Level