Software Engineer III, Java, AWS

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Consumer and commercial Banking you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm s business objectives.

Job Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Own delivery of multi-sprint outcomes: drive work from requirements through design, implementation, testing, documentation, release, and production support, managing dependencies and risks.
• Lead service and API design decisions (component/service level), including backward compatibility/versioning, performance/scaling basics, caching strategies, concurrency patterns, and reliability tradeoffs.
• Set and raise engineering standards for clean code, reviews, testing practices, and maintainable designs; ensure consistent adoption across the team.
• Drive quality engineering and automation: define test strategy (unit/integration/contract), improve CI/CD safety, strengthen static analysis, and reduce regressions through tooling and process improvements.
• Champion operational excellence: improve observability (logs/metrics/traces), define/track reliability signals, lead incident response and RCAs, and implement durability/resiliency enhancements to prevent recurrence.
• Embed security, risk & controls into delivery: promote secure coding practices, access control principles, dependency/vulnerability hygiene, correct data handling, and disciplined change management.
• 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.
• Partner with Product, QA, SRE/Production Engineering, Security, and adjacent engineering teams to align on outcomes, communicate tradeoffs, and influence technical direction, while mentoring engineers, supporting hiring/technical evaluation, and driving continuous improvement in team practices.

Required qualifications, capabilities, and skills

• 5+ years Experience to cloud technologies such as AWS, Azure, and/or GC with experience building and operating services in cloud environments.
• 5+ years of experience in least one core language (e.g., Java, Kotlin, Python, TypeScript) with strong CS fundamentals (DS&A, OO/design, clean coding).
• Demonstrated experience designing and building APIs and services, with strong practical knowledge of performance, scaling basics, caching, and concurrency.
• Strong testing and delivery discipline: unit/integration/contract testing, CI/CD usage, code review rigor, and automation-first mindset.
• Proven operational mindset: observability practices, production support/on-call participation, incident triage, and deep RCA with follow-through improvements.
• Strong security and risk/control awareness in a regulated environment (secure coding, access control, dependency hygiene, data handling, change management).
• Strong collaboration and communication skills; ability to drive alignment and execution across multiple stakeholders.
• 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…