Lead Software Engineer - Java, Python, AWS

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 the Corporate and Investment Banking (CIB) Payments Technology team, you play a crucial role in an agile team that is dedicated to improving, creating, and delivering trusted market-leading technology products in a secure, stable, and scalable manner. As a key technical contributor, you are tasked with implementing vital technology solutions across numerous technical areas within various business functions to support the firm's business goals.

As a Regulatory Reporting Lead engineer, you will be accountable for end-to-end technical delivery across Regulatory initiatives. You will also help shape how the team applies modern data platforms (Databricks, Spark) and AI-assisted engineering to reporting workloads.

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 and high-quality production code, and reviews and debugs code written by others
• Build and optimize large-scale data and reporting pipelines on Databricks/Spark, including data quality, lineage, and reconciliation controls for regulatory submissions
• Applies AI and machine-learning techniques and AI-assisted engineering tools to accelerate delivery and automate reporting and remediation workflows
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Closely work with external vendors, 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
• 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

Required qualifications, capabilities, and skills