Full Stack Engineer | New York, US

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. 

Required Qualifications 

• 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.