As a Lead Software Engineer at JPMorgan Chase within Securities Lending, youare 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 developing critical technology solutions across multiple technical domains within various business functions in support of the firm27s 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
• Creating user interfaces and interactive features for web applications using languages and frameworks.
• 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
• Leads evaluation sessions with 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
• Uses enterprise-authorized AI capabilities within the work environment to accelerate program planning and risk synthesis (e.g., consolidating inputs into integrated plans, RAID, and executive-ready updates), validating outputs and handling data according to sensitivity requirements.
• Promotes reuse-first, AI-assisted practices for program governance and reporting, ensuring human review and alignment to delivery standards.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Experience in software development of Micro services with Java, Spring Boot, Python
• Experience with cloud technologies and distributed systems, RESTful APIs and web technologies. Knowledge of Restful Web Services,WebSockets; JSON
• Hands-on experience designing and building enterprise-scale, high-volume data processing applications using SQL databases such as Oracle.
• Advanced Proficiency in front-end languages and libraries (e.g.C#, React) and back-end languages and frameworks (e.g., Java, Spring, Python etc.) and practical cloud native experience.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Experience with build and Integration Tools, including knowledge of JIRA, Maven, Git, Jenkins, GitHub and BitBucket is required.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, etc.)
• 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 resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills

• Experience working across the entire Software Development Life Cycle in a large corporate environment.
• Completed AWS Developer or Solution Architect Certification
• In-depth knowledge of the financial services industry and their IT systems
• Observability and production management tools (ex. Splunk / Dynatrace / Grafana)
• A keen interest in staying ahead of modern development trends and experimenting with emerging technologies such as AI and Machine Learning