Lead Software Engineer - Backend Engineering, Java

Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center -  all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment. 

As a Lead Software Engineer at JPMorgan Chase within the Accelerator business, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.

While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world.

Job responsibilities:

• Use domain modeling techniques to allow us to build best in class business products.
• Structure software so that it is easy to understand, test and evolve.
• Build solutions that avoid single points of failure, using scalable architectural patterns.
• Develop secure code so that our customers and ourselves are protected from malicious actors.
• Promptly investigate and fix issues and ensure they do not resurface in the future.
• Make sure our releases happen with zero downtime for our end-users.
• See that our data is written and read in a way that's optimized for our needs.
• Keep an eye on performance, making sure we use the right approach to identify and solve problems.
• Ensure our systems are reliable and easy to operate.
• Keep us up to date by continuously updating our technologies and patterns.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.

Required qualifications, capabilities and skills:

• Formal training or certification on problem-solving concepts and proficient applied experience
• Identifies problems, proposes solutions, suggests what's best to focus on. Sees themselves as a problem solver. 
• Contributes to the problem at hand, even when outside their area of speciality.
• A desire to teach others and share knowledge. We aren’t looking for hero developers,  more for team players.
• Adjusts quickly to changing priorities and conditions. Copes effectively with complexity and change. Learns and unlearns technologies and patterns quickly. Comfortable in uncharted waters.
• Can see the long term. Won’t sacrifice the future for the present. Chooses technologies and approaches based on the end goals.
• High standards. Expects personal performance and team performance to be nothing short of the best.
• Does not cut corners ethically. Earns and maintains trust.
• Does what's best for the company, rather than what's best for themselves or their team.
• Able to take the initiative and shape their own path and a pragmatic and iterative approach to achieving our long term goals
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Technologies:

• We primarily use Jvm based languages (Java/Kotlin) but we also have parts of the platform that use other languages as needed.
• We look to use Open source when it makes sense and build ourselves when it doesn't.
• We are entirely cloud native and want to build a truly multi-cloud solution.
• We look at each problem independently and pick the right technology to solve it.

• We aren’t afraid to try new things but we always remember that we are looking to build something to last, and we focus on solving real world problems for real life customers.

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