Java AI Lead Software Engineer

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As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Branch Operations 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
• 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.
• 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
• Owns end-to-end DevOps execution for the team’s SDLC, including Jenkins and Spinnaker pipelines, release practices, environment promotion strategy, and automated quality gates.  
• Defines and enforces comprehensive testing strategy across the stack (unit, contract, component, functional, performance, and resilience testing), including consistent test data/environment approaches and measurable coverage/quality outcomes.  
• Leads design and implementation of Java-based microservices and back-end APIs (REST/event-driven), ensuring scalability, resiliency, and secure-by-default patterns across services
   

 

 

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
• 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
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• 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
• Strong hands-on experience building and supporting Java services and APIs REST/OpenAPI and familiarity with observability stacks (e.g., Splunk, CloudWatch, Prometheus/Grafana, OpenTelemetry), including performance tuning, debugging, and production support in distributed systems
• Practical experience with data and messaging platforms such as Cassandra (data modeling, reliability, operational patterns) and Kafka (producer/consumer patterns, delivery semantics, and monitoring)
• Proven experience delivering and operating applications in Private Cloud (GAIA) and/or AWS hosting, including secure configuration, resilience patterns, and operational readiness for production

 Preferred qualifications, capabilities, and skills 

• Experience building and shipping native Android applications (preferred: Kotlin/modern Android patterns) including release management, CI/CD integration, and app observability
• Experience developing and operating React front-end applications (preferred: TypeScript), including integration with back-end APIs and end-to-end quality practices  
• Experience with safe rollout strategies (shadowing, A/B testing, progressive exposure), human-in-the-loop review, and continuous evaluation for quality and safety, including canary rollouts
• Knowledge of API gateways, service mesh, and multi-region high availability and disaster recovery for mission-critical services
• Familiarity with data privacy, security best practices, and regulatory compliance in financial services    
• Experience with performance optimization, scalability, and reliability engineering for large-scale systems
• Ability to evaluate and integrate third-party tools, libraries, and frameworks to accelerate development