Lead Software Engineer - Python

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 Infrastructure Platforms - Core Foundational Platforms / Databases, you will be an integral part of a global agile engineering team responsible for designing, building, and delivering secure, stable, scalable, and highly automated database platform capabilities across the firm. The Cloud Relational Database Team develops automation, self-service capabilities, and engineering solutions that support database provisioning, build, deployment, lifecycle management, and operational efficiency for enterprise database platforms.

In this role, you will contribute to and lead engineering efforts for database automation and platform services. You will work closely with product owners, database engineering teams, infrastructure teams, application development teams, and site reliability teams to deliver modern, resilient, and developer-friendly database services.

You will be expected to bring strong software engineering practices, automation-first thinking, and technical leadership to solve complex infrastructure and database platform challenges at enterprise scale.

Job responsibilities

• Design, develop, test, deploy, and maintain high-quality software solutions that automate database build with deployment, provisioning, configuration, lifecycle management, and operational workflows

• Build and enhance self-service capabilities for database platforms used across the firm to enable faster delivery, improve developer experience, and reduce operational toil

• Develop secure, reliable, and scalable backend services, APIs, automation frameworks, user interfaces, and orchestration workflows using technologies such as Python, React, Django, Ansible, Terraform and other related engineering tools

• Execute creative software solutions in designing, developing and technical troubleshooting, thinking beyond routine or conventional approaches to solve complex technical problems

• Produce secure, high-quality code, perform code reviews, debug complex issues, and provide technical guidance to other engineers

• Identify opportunities to eliminate manual processes and automate remediation of recurring issues to improve the operational stability, resiliency, and efficiency of database platforms and supporting applications

• Partner with database engineering, cloud, infrastructure, cybersecurity, and application teams to deliver solutions that align with firmwide architecture, resiliency, control, and security standards

• Contribute to the modernization of database build and deployment capabilities, including cloud-enabled patterns, infrastructure-as-code, continuous delivery, and self-service operating models

• 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

• 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 in system design, application development, testing, deployment, and operational stability

• Advanced hands-on programming experience in one or more programming languages(s) and framework(s) (i.e., Python, Automation, Rest API, Platform tooling, etc.)

• Strong understanding of software engineering principles, including object oriented design, API development, automated testing, code quality, version control, and production support

• Experience building automation solutions, platform services, backend applications, workflow orchestration, or infrastructure engineering tools

• Proficiency in automation and continuous delivery practices, including CI/CD pipelines, release autmation, deployment tools in Jenkins and Spinnaker, release management, and environment promotion

• 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

• Proficiency across the Software Development Life Cycle, including requirements analysis, design, development, testing, deployment, monitoring, and support

• Strong analytical, troubleshooting, and problem-solving skills, with the ability to break down complex technical issues and drive them to resolution

• Excellent verbal and written communication skills, with the ability to communicate technical concepts clearly to engineering teams, stakeholders, and leadership

• Ability to work effectively in a global team environment, collaborate across functions, and provide technical leadership to other engineers

Preferred qualifications, capabilities, and skills

• Knowledge of relational database management systems, RDBMS technologies such as Oracle, PostgreSQL and MySQL

• Experience with modern front-end technologies, especially React, JavaScript, TypeScript, HTML, and CSS

• Hands-on experience with automation and infrastructure-as-code tools such as Ansible and Terraform

• Experience with asynchronous job processing, workflow orchestration, or distributed task execution using tools such as Celery

• Knowledge/exposure to AWS cloud services, cloud-native design patterns, and infrastructure-as-code practices

• Experience working in Linux-based environments, including shell scripting, troubleshooting, and system-level diagnostics

• Experience using modern developer tools such as IntelliJ, VS Code, Git, and GitHub Copilot