Lead Software Engineer - Reliability & Support

As a Lead Software Engineer at JPMorgan Chase within the Test Integration and Implementation Payments Technology Team in the Corporate & Investment Bank line of business, you serve as a seasoned member of an agile team to support, design and deliver trusted market-leading technology products in a secure, stable, and scalable way.

You are responsible leading critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Required qualifications, capabilities, and skills


* Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.


* Leads initiatives to improve the reliability and stability of the applications and platforms using data-driven analytics to improve service levels, proactively identifying and solving technology-related bottlenecks in areas of expertise


* Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development


* Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems


* Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture


* Contributes to software engineering communities of practice and events that explore new and emerging technologies


* Adds to team culture of diversity, equity, inclusion, and respect.


* 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.


* Ability to apply Agentic AI frameworks to automate and augment core Environment Management functions such as intelligent incident detection and remediation, automated root cause analysis, predictive alerting, self-healing infrastructure, runbook automation, and observability enrichment to reduce toil and accelerate MTTR.


* Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls.
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.

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts an...