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 Commercial and Investment Banking - Applied AI/ML team, 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. 

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 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 sessions with internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and on-prem/cloud 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, equity, opportunity, and respect 

Required qualifications, capabilities, and skills 

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

• Extensive experience in building and running AWS/public cloud based applications 

• Solid programming skills with Python 

• Hands-on practical experience delivering system design, application development, testing, and operational stability 

• Proficiency in automation and continuous delivery methods and all aspects of the Software Development Life Cycle 

• Experience of pipelines and DAG's (Directed Acyclic graph) for processing data and/or machine learning 

• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence and machine learning.) 

• In-depth knowledge of the financial services industry and their IT system