Lead Software Engineer - Python​/React, Ansible, RHEL

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 JPMorgan

Chase within Asset & Wealth Management, 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.

We are seeking a Vice President, Software Engineering to lead the design, development, and support of automation-enabled software solutions. This role requires deep Python expertise, strong React experience, hands‑on knowledge of Ansible Automation Platform, and operational familiarity with Red Hat Enterprise Linux (RHEL). The VP will partner closely with internal customers/users, own production outcomes, and drive improvements in reliability, usability, and delivery practices.

Basic networking knowledge is preferred (e.g., DNS, TLS/certificates, connectivity troubleshooting).

• Own end-to-end delivery of software capabilities using Python (services, APIs, integrations, automation tooling) and React (UI workflows, API-driven front‑ends).

• Drive design decisions and establish engineering standards (code quality, testing strategy, CI/CD patterns, release discipline).

• Build and scale automation and tooling capabilities to improve operational efficiency and user experience.

• Diagnose common integration and connectivity issues using basic networking fundamentals (e.g., DNS, TCP connectivity concepts, TLS/certificates), escalating to specialist teams when needed.

• 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.

• Develop and maintain automation solutions using Ansible Automation Platform (playbooks/roles, inventories, credential patterns, operational runbooks).

• Lead effective customer support practices: incident/ticket triage, prioritization, clear communications, root‑cause analysis, and prevention plans.

• Troubleshoot issues on RHEL (service health, logs, permissions, performance basics) and coordinate resolution across partner teams.

• Partner with product, infrastructure/platform, security, and operations stakeholders to deliver outcomes and manage risk.

• Maintain documentation, runbooks, and knowledge content; drive continuous improvement to reduce recurring issues and toil.

• Formal training or certification on software engineering concepts and 5+ years applied experience

• 5+ years of professional experience in Python, React, Automation software engineering experience.

• Deep Python engineering experience (production‑grade code, debugging, testing, API integrations).

• Strong experience building web applications with React (component design, state management, API integration).

• Hands‑on experience with Ansible Automation Platform (or enterprise‑scale Ansible automation in a managed platform context).

• Practical experience supporting systems on Red Hat Linux / RHEL.

• 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…