Lead Software Engineer Python

JPMorgan Chase & Co.•Houston, TX

About The Position

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within CORPORATE SECTOR - CORPORATE TECHNOLOGY, you are 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 delivering critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Requirements

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; front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).
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, including RESTful 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
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
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

Nice To Haves

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.

Responsibilities

Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.
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.
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.
Promptly investigate and resolve issues, ensuring they do not resurface.
Design and build solutions that avoid single points of failure using scalable architectural patterns.
Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.