JAVA Engineer

The Full Stack Engineer will design, build, troubleshoot, and support secure, high-quality production software across backend, frontend, cloud native, and automation domains. The role emphasizes hands-on application development, operational stability, microservices, CI/CD, resiliency, security, responsible AI-assisted engineering practices, and leadership in reusable patterns, technical guidance, and engineering community adoption.

Core Responsibilities

• Execute creative software solutions, design, development, and technical troubleshooting while thinking beyond routine or conventional approaches to solve technical problems.
• Develop secure, high-quality production code and review, debug, and improve code written by others.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability across applications and systems.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Establish validation standards for AI-assisted engineering outputs, including secure coding, peer review, automated testing, and expectations for correctness, performance, and security.
• Apply SDLC toolchain knowledge, including approved AI-assisted development and automation capabilities, to improve the value realized from automation.
• Lead evaluation sessions with external vendors, startups, and internal teams, probing architectural designs, technical credentials, and fit within existing systems and information architecture.
• Lead communities of practice across Software Engineering to increase awareness and adoption of new and leading-edge technologies.
• Provide technical guidance and direction to business teams, technical teams, contractors, and vendors.
• Drive decisions influencing product design, application functionality, technical operations, and engineering processes.
• Serve as a subject matter expert in one or more technical focus areas and advocate for firmwide frameworks, tools, and SDLC practices.
• Contribute to an engineering culture grounded in diversity, opportunity, inclusion, and respect.

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Proficiency in Java, Spring Boot, Docker, Kubernetes, Cassandra or other NoSQL databases, and at least one frontend technology such as React, ReactJS, Redux, Angular, AngularJS, ExtJS, JQuery, or NodeJS.
• Hands-on experience with microservices and RESTful microservices development.
• Experience with messaging and integration frameworks such as Kafka.
• Experience developing with testing frameworks such as JUnit, Mockito, Karma, Protractor, Jasmine, Mocha, Selenium, and Cucumber.
• Proficiency in automation and continuous delivery methods.
• Proficiency across the Software Development Life Cycle.
• Advanced understanding of agile methodologies, CI/CD, application resiliency, and security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile.
• In-depth knowledge of financial services industry technology systems.
• Practical cloud native experience in AWS.
• Ability to tackle design and functionality problems independently with little to no oversight.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools for coding, code review, test acceleration, troubleshooting, release readiness, or incident/root-cause analysis.

• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, resiliency, security expectations, and compliant adoption controls. Preferred Qualifications

• Experience working in a financial services environment.
• Technology coaching and leadership experience helping teams solve complex technology problems.
• Experience coaching engineers, senior engineers, or technical leads on safe, compliant AI-assisted software development usage patterns.

• Experience promoting reuse of proven patterns, automation, and engineering practices across teams. Operating Environment and Delivery Expectations

• Operate as both a hands-on engineer and technical leader across application development, troubleshooting, automation, operational stability, and technical governance.
• Balance delivery acceleration from AI-assisted development practices with required validation controls, secure coding discipline, peer review, automated testing, and measurable standards.
• Support modernization and production reliability across backend services, frontend technologies, microservices, cloud native infrastructure, and CI/CD delivery practices.
• Engage vendors, startups, internal teams, contractors, and business partners through architecture evaluation, technical guidance, and outcomes-oriented decision support.
• Contribute to broader engineering effectiveness through communities of practice, firmwide tools, reusable patterns, and adoption of leading-edge technologies.