Lead Software Engineer- Python / AI

JPMorgan Chase & Co.; Houston (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorganChase in Houston seeks a Lead Software Engineer to advance trusted market-leading technology products within a secure, scalable framework. You will be a core technical contributor across multiple domains within the Corporate Sector, delivering solutions and driving AI-assisted engineering practices.

The role requires 5+ years of software engineering experience, strong Python skills, and experience across the full SDLC in a large corporate environment.

Qualifications

• 5+ years of software engineering experience with formal training or certification.

Responsibilities

• Execute innovative software solutions and troubleshoot complex problems.
• Develop secure, high-quality production code and review others’ code.
• Promote enterprise AI-assisted engineering practices to improve quality, speed, and reliability.
• Leverage SDLC tools and automation to enhance value and efficiency.
• Identify and automate recurring issues to improve stability of applications.
• Lead evaluation sessions with vendors and teams to assess architectural designs.

Skills

Python

Software design

CI/CD

AI-assisted development

Agile

Cloud

Security

Tools

SDLC tooling

Job description

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 the Corporate Sector, 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 conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Demonstrable expertise to code in Python
• Experience across the whole Software Development Life Cycle
• Expertise in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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 knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• 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
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as Continues Integration and continues develoop, Application Resiliency, and Security
• In‑depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience

Preferred qualifications, capabilities, and skills

• Familiarity with modern front‑end technologies: UI, React
• Exposure to cloud technologies: AWS
• Exposure to Banking/Finance or Risk domains