Java AI Lead Software Engineer

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 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