JPMorgan Chase & Co.

Lead Software Engineer -Java Backend, Kafka- Payment Technology

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

9 h ago
Senior (5-10 yrs) Full-time India
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About the role

Lead the design and development of secure, scalable payment technology solutions within an agile team. Drive the adoption of AI-assisted engineering practices and ensure high operational stability for critical financial systems.

What they look for

Java Spring Boot Kafka System Design Payment Technology ACH Cloud Native CI/CD AI-assisted Engineering API Design Resiliency Patterns Agile Methodologies JVM Tuning Financial Services IT Observability Software Architecture

Requirements

Requires 5+ years of software engineering experience with expert-level Java and Spring Boot skills. Deep hands-on expertise in payments domain (ACH, wires) and cloud-native system design is essential.

Full description

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

Preferred qualifications, capabilities, and skills

  • 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