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 JPMorganChase within the Consumer and Community Banking, 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 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 3+ years applied experience.
- Proficiency designing and implementing data pipelines for both batch and streaming use cases using Spark and public cloud-native technologies.
- Experience developing applications on AWS, leveraging services such as Lambda, S3, Glue, Step Functions, Airflow, and integrating with enterprise data platforms such as Snowflake and Databricks.
- Strong Python development skills, including AI development with a focus on agentic systems.
- Ability to independently design and implement complex logic, algorithms, and workflows for scalable distributed systems
- Hands-on experience with CI/CD automation and build pipelines/tools (e.g., Git, Jenkins, Maven) and AI-assisted coding tools
- Proficiency with large-scale data processing frameworks (e.g., PySpark), including knowledge of data pipeline design, data modeling, data warehousing, and data migration
- Advanced SQL skills (e.g., joins, aggregations) and working knowledge of NoSQL databases.Experience building distributed applications, event-driven systems, and real-time processing pipelines.
- Significant experience with statistical data analysis, including selecting appropriate analytical methods and tools for a given problem.
- 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 developing applications on AWS, leveraging services such as Lambda, S3, Glue, Redshift, Step Functions, and related services to build scalable, reliable systems.
- Hands-on experience delivering system design, application development, testing, and operational stability.
- Advanced proficiency in Python (or another primary programming language).
- Strong analytical and problem-solving skills.
- Solid foundation in object-oriented programming and software engineering fundamentals.
- Strong understanding of Agile delivery and engineering practices, including CI/CD, application resiliency, and security principles.