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As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - AIML Solutions technology, 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 standard software solutions, design, development, and technical troubleshooting
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.
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
- Hands on code development to enable our AI/ML platform, ensuring robustness, scalability, and high performance.
- Adopt the best practices in software engineering, machine learning operations (MLOps), and data governance.
- Maintain consistent code check-ins every sprint to ensure continuous integration and development.
- Executes using Platform engineering to enable the Gen AI platform and develop the Gen AI Use cases ,LLM fine tuning and multi agent orchestration.
- Communicate technical concepts and solutions effectively across all levels of the organization.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 5 + years of applied 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
- Extensive practical experience with Python and AWS cloud services, including EKS, EMR, ECS,
- Hands-on experience in AIML lifecycle development.
- Advanced knowledge in Generative AI, Agent development and the AI platform engineering