We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Sr Lead Software Engineer at JPMorgan Chase within the Chief Data and Analytics Office, youare 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
- Execute creative software solutions, design, development, and technical troubleshooting for AI‑enabled applications.
- Develop secure, high‑quality production code; review and debug SDK and service integrations.
- 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.
- Identify and automate remediation of recurring issues to improve reliability of AI features and services.
- Lead evaluation sessions with vendors and internal teams on model capabilities, safety, and integration patterns.
- Lead communities of practice to share prompt engineering, evaluation methods, and SDK best practices.
- Add to team culture of diversity, opportunity, inclusion, and respect.
- Build and ship AI‑powered features using AI (Bedrock or Foundry or Vertex AI), including prompt design, function calling, and SDK/REST integrations (no prior experience required).
- Implement input/output safety (guardrails, moderation) and comprehensive LLM usage logging/monitoring (no prior experience required).
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience.
- DevOps: CI/CD pipelines, infrastructure as code, containerization/orchestration, observability, and cloud platforms AWS, GCP, Azure
- Hands‑on experience delivering system design, application development, testing, and operational stability.
- Advanced proficiency in Python software engineering skills
- 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
- Proficiency in automation and continuous delivery methods; strong unit/integration testing discipline.
- Proficient in all aspects of the Software Development Life Cycle and secure coding practices.
- Advanced understanding of CI/CD, application resiliency, and security for AI applications.
- Practical cloud‑native experience.
Preferred qualifications, capabilities, and skills