Lead Software Engineer - Python, Cloud & AI

Jpmorganchase
UK
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Java (Programming Language) Agile Methodology Artificial Intelligence Software Applications Automation of Tests Cloud Computing Software Quality Code Review Continuous Integration Data Validation Extract Transform Load (ETL) Python (Programming Language)
+10 more
Software Tools Secure Coding Software Engineering Software Systems Strategies of Testing Toolchain Production Code Code Restructuring Data Pipelines Programming Languages

Job description

Are you ready to make a real impact in cloud financial management technology? At JPMorganChase, you’ll collaborate with talented teams to deliver secure, scalable, and market-leading products. Here, you can push the boundaries of what’s possible while growing your skills and advancing your career. We value creativity, innovation, and a passion for technology. Join us and be part of a team where your contributions matter. As a Lead Software Engineer at JPMorganChase within the Cloud Financial Management technology team, you will play a key role in designing and delivering trusted technology solutions. Working within an agile environment, you will collaborate with diverse teams to support the firm’s business objectives, drive technical excellence, and foster a culture of innovation and continuous improvement. Together, we’ll build solutions that make a meaningful difference. Job responsibilities Executes creative software solutions, design, development, and technical troubleshooting

Requirements

with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Develops secure and high-quality production code, and reviews and debugs code written by others 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. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Hands-on experience delivering system design, application development, testing, and operational stability Advanced proficiency in one or more programming languages, including Python or Java Proficiency in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, application resiliency, and security Practical cloud-native development experience Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Hands-on experience building and operating data pipelines (e.g., ETL/ELT patterns, orchestration/scheduling, monitoring, and data quality checks) in a production environment Preferred qualifications, capabilities, and skills Experience leading engineering teams within a large, complex organization Familiarity with modern cloud technologies and deployment practices Experience mentoring and coaching engineers at varying levels Knowledge of industry-wide technology trends and best practices Experience with financial management platforms or related domains #J-18808-Ljbffr

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