Senior, Expert
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As a Lead Software Engineer at JPMorganChase within the Data Management/Data Tech, 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
Lead with an AI-driven approach in daily tasks
Spearhead the design and development of real-time, mission-critical using Java
Tackle large-scale engineering challenges with technologies like Kafka
Innovate, troubleshoot, and optimize for performance and stability
Inspire and foster a culture of creativity, inclusion, and technical excellence
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
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
5+ years of relevant software engineering experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)
Proficiency in automation and continuous delivery methods
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience
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:
Expertise in GenAI usage, transforming Software Engineering with an AI-first approach
Experience with both Java and Python development
Proficiency in Java/Spring, data structures, AWS, Terraform and performance tuning
Solid experience with Kafka
Proficiency in testing and debugging low latency applications
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