Java AI Lead Software Engineer

JPMorgan Chase & Co.•Westerville, OH

About The Position

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.

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
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

Nice To Haves

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

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