Lead Software Engineer Python Full Stack, AIML

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank youare an integral part of an agile team that works to enhance build and deliver trusted market-leading technology products in a secure stable and scalable way. As a core technical contributor you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

• Executes creative software solutions design development and technical troubleshooting thinking beyond routine or conventional approaches to build solutions or break down technical problems.
• Delivers end-to-end solutions in the form of cloud-native microservices-based applications leveraging the latest technologies and best industry practices.
• Uses domain modeling techniques to build best-in-class business products structuring software for clarity testability and evolution.
• Develops secure high-quality production code and reviews and debugs code written by others.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity opportunity inclusion and respect. Investigates and resolve issues ensuring they do not resurface.
• Designs and build solutions that avoid single points of failure using scalable architectural patterns. Designs and build scalable secure and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
• 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 software engineering concepts and 5 years applied experience
• Proficiency in back-end technologies (e.g. Python Flask Django) with experience building microservices-based applications; for full-stack roles proficiency also includes front-end technologies (e.g. HTML CSS JavaScript Typescript React Angular).
• Well versed with AI/ML technologies (e.g. LLM AI Python libraries LLM tools ML foundations)
• Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
• Experience working with cloud platforms (e.g. AWS Azure GCP) distributed systems and web technologies includingRESTful APIs and web services WebSockets and JSON.
• Hands-on experience designing and building scalable applications using SQL and NoSQL databases. Experience with agile development methodologies (e.g. Scrum) and an understanding of the software development life cycle.
• Understanding of application resiliency. Proficiency in automation and continuous delivery methods.
• Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as CI/CD Application Resiliency and Security.
• 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

• Strong soft skills including presentation negotiation mentoring and stakeholder management.
• Strong problem-solving analytical and communication skills.
• Ability to drive broader impact by sharing and contributing best practices.
• Experience in the banking domain. AWS certification.