Senior Lead Software Engineer - Java Architect

JPMorgan Chase & Co.•Palo Alto, CA

12d•$175,750 - $260,000

About The Position

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions. As a Software Engineer III at JPMorganChase within Commercial and Investment Bank - Payments Technology, you serve as a seasoned member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will deliver both the technical platform capabilities and the business functionality that process payments for global clients across multiple clearing systems, building high-volume, event-driven microservices and APIs where correctness, resiliency, and auditability are critical.

Requirements

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
Hands-on programming experience with Java, Spring Boot, and microservices architecture
Experience designing and building RESTful APIs, including API security, authentication/authorization, and API documentation
Experience with event-driven and messaging platforms such as Kafka or IBM MQ
Experience with relational databases (e.g., Oracle) and NoSQL data stores, including SQL and database schema change management
Experience with automated testing (TDD, JUnit, Mockito, BDD/Cucumber) and CI/CD pipelines (e.g., Maven, Jenkins)
Experience deploying and operating services using Docker and Kubernetes
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Solid understanding of agile practices, application resiliency, and security

Nice To Haves

Exposure to payments or financial services technology (e.g., payment processing, clearing and settlement, fraud or sanctions screening)
Experience with event sourcing, state machine–based workflows, or high-throughput transaction processing
Experience with gRPC and Protobuf
Experience with Python for automation, internal tooling, or data analysis and reporting
Experience with observability tooling (e.g., OpenTelemetry, Grafana)
Familiarity with modern front-end technologies (e.g., JavaScript, HTML/CSS)

Responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Partners with product owners, business analysts, and operations teams to translate payment business requirements such as validations, enrichment, routing, and exception handling into robust technical solutions
Designs, develops, and maintains Java/Spring Boot microservices and RESTful APIs that process payment transactions through Kafka- and MQ-based event-driven flows
Creates secure and high-quality production code, including stateful workflows, idempotent message processing, and resilient integrations with upstream and downstream systems
Writes automated unit, integration, and end-to-end tests and contributes to CI/CD pipelines with static analysis and code quality gates to deliver safe, frequent releases
Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Supports production stability through monitoring, troubleshooting, and root-cause analysis of payment flows in containerized, Kubernetes-based environments
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness
Analyzes production telemetry and operational data to proactively identify hidden problems and patterns, and uses these insights to drive improvements to coding hygiene and system architecture