Trading Platform Engineer II — High-Performance Java GenAI

JPMorgan Chase Bank, N.A.; Hong Kong; On-site; HKD 700,000 - 900,000; Full time

Job summary

JPMorgan Chase Bank, N.A. is seeking a Software Engineer II in Asset Management Trading Technology to design, build, and evolve platforms that manage orders and execute trades across asset classes.

You will work with Traders to support production-critical applications and automate the order-management lifecycle. Participation in full SDLC, emphasis on scalable, reliable systems, and adoption of GenAI practices are core.

Qualifications

• Bachelor’s Degree in Computer Science or equivalent.
• Formal Training and certification on software engineering and 3+ years of applied experience.
• Proven hands-on experience designing and building end-to-end software systems.
• Strong knowledge of core Java and object-oriented design principles. Kotlin nice to have.
• Experience with messaging and streaming technologies e.g. Kafka.
• Solid understanding of modern software architecture and design patterns.
• Demonstrated ability to work in a fast-paced environment.
• Commitment to building reliable, scalable, and maintainable systems.
• Ability to collaborate effectively with cross-functional teams including Traders and Quants.
• Passion for code quality, engineering excellence, and elegant solutions.
• Dedication to continuous improvement and rapid delivery.
• Strong problem-solving skills and creative thinking
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Responsibilities

• Support critical applications in production, interacting directly with users to resolve issues.
• Design and engineer scalable, high-performance trading systems across multiple asset classes.
• Collaborate directly with Traders to deliver impactful solutions.
• Build and develop core Java applications for mission-critical trading platforms.
• Architect and implement next-generation messaging and streaming technologies such as Kafka and AMPS.
• Drive technical innovation and contribute creative ideas for platform advancement.
• Drive the adoption and scaling of GenAI practices within the software development workflow, bringing creative ideas on how to use AI tooling effectively and reliably.
• Lead code reviews and mentor team members to ensure engineering excellence.
• Participate in the full software development lifecycle from design through to production.
• Focus on continuous improvement and fast, iterative delivery.
• Deploy code to production daily with confidence.
• Add to team culture of diversity, opportunity, inclusion, and respect.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• 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.

Job description

JPMorgan Chase Bank, N.A. is seeking a Software Engineer II in Asset Management Trading Technology to design, build, and evolve platforms that manage orders and execute trades across asset classes.

You will work with Traders to support production-critical applications and automate the order-management lifecycle. Participation in full SDLC, emphasis on scalable, reliable systems, and adoption of GenAI practices are core.