Lead Software Engineer - Python/Django

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorganChase in Plano, TX seeks a Lead Software Engineer to join Infrastructure Platforms. You will be a core technical contributor, delivering trusted market-leading technology that is secure, stable, and scalable across multiple business functions.

You will drive architectural discussions, automate deployments, and mentor teams to adopt enterprise AI-assisted engineering practices while ensuring secure coding and robust testing standards.

Qualifications

• Formal training or certification in software engineering with 5+ years experience.
• Proficiency in Python and Django or related frameworks.
• Automation, CI/CD, and delivering resilient systems.

Responsibilities

• Develop secure high-quality production code and review code written by others.
• Advise on AI-assisted engineering practices to improve code quality and delivery speed.
• Lead architectural discussions and evaluate external vendors/teams for implementation feasibility.
• Promote best practices across the team for secure coding, testing, and reliability.

Skills

Python

CI/CD

Cloud platforms

AI/ML concepts

Security

Agile methodologies

Kubernetes

Tools

Terraform

AWS

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 Infrastructure Platforms, 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 break down technical problems
• 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
• 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 and 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 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
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Advanced in one or more programming language(s) and framework(s) (e.g., Python, Django, etc.)
• Proficiency in automation and continuous delivery methods and hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient in all aspects of the Software Development Life Cycle and must have 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.)
• 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, with enterprise authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• Proven expertise in designing, deploying, and managing containerized distributued applications, with a strong understanding of orchestration and scaling strategies.
• Demonstrated ability to architect and manage infrastructure on AWS Cloud, utilizing Infrastructure as Code (IaC) tools like Terraform to automate and optimize deployment processes.
• Proven experience in designing and implementing control plane architectures for large-scale applications, focusing on efficient resource management, orchestration, and system reliability to support complex, distributed systems.
• In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

• Hands-on experience with relational databases, particularly CockroachDB or similar distributed databases, ensuring data consistency, reliability, and performance in distributed environments.
• Practical cloud native experience