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 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.
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