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 Corporate Sector's AI/ML & Data Platforms 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
- Designs and implements secure Data Lake solutions within the AWS environment.
- IaaS (Infrastructure As A Code) development including Terraform configuration script, Python scripts or Java programming to create services and resources in AWS Cloud environment.
- Explores and evaluates new Data Management features offered by AWS.
- 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, MCP server creation, 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.
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Collaboration with different teams to execute software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on experience in AWS, especially in Data Management arena such as Glue, EMR, Athena, Redshift, and Lake Formation.
- Proficient in Python, Java, and database query languages for applications development, debugging, and maintenance in a large corporate environment
- 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
- Overall solid knowledge of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
- Hands-on Terraform or other IaaS experience
- AWS certification on Solutions Architect Associate / Developer level
- Other advanced level certification on programming languages.
- Knowledge working with PCI and sensitive data workloads