Full Stack Java Developer - W2 Role

Role:
Full Stack Java Developer - W2 Role

Location:
New York, NY (Onsite)

H1B transfers are acceptable

Position Summary

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.

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 No
  
  SQL 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.