Sr. Lead Software Engineer - Java/ Python

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

JPMorganChase in the Data Technology space seeks a Senior Lead Software Engineer to guide an agile team in building trusted, scalable financial technology products for Consumer and Community Banking. You will drive secure coding, code reviews, and AI-assisted engineering practices, mentoring senior engineers and shaping SDLC standards.

The role emphasizes cloud-native engineering, enterprise tooling adoption, and delivering resilient software solutions with a focus on security and performance.

Qualifications

• Formal training or certification in software engineering with practical 5+ years of applied experience.
• Experience delivering system design, application development, testing, and operational stability.
• Advanced programming skills in Java, Python, or Go with strong AWS cloud experience.
• Experience leading use of AI-assisted development tools and setting team expectations for outputs.

Responsibilities

• Provides technical guidance to business teams, contractors, and vendors.
• Develops secure, high‑quality production code and reviews peers' work.
• Drives adoption of AI-assisted engineering practices with measurable validation standards.
• Applies SDLC toolchain knowledge to improve automation and reliability.
• Influences product design, functionality, and technical operations.
• Serves as a subject‑matter expert across focus areas and promotes firmwide practices.

Tools

Docker

CI/CD

Job description

Be an integral part of an agile team that’s constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer at JPMorganChase within the Consumer and community banking in Data Technology space, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem‑solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI‑assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI‑assisted code review/refactoring, test acceleration, release readiness, incident/root‑cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI‑assisted development and automation capabilities, to improve the value realized by automation at scale.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function‑wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language - Java or Python or Go along with strong AWS cloud experience.
• Demonstrated experience leading effective use of enterprise‑authorized AI‑assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
• Ability to tackle design and functionality problems independently with little to no oversight
  Practical cloud native experience

Preferred qualifications, capabilities, and skills

• Experience with messaging systems
• Experience with Docker and containerization best practices. Familiarity with CI/CD tools.
• Understanding of security best practices and secure coding principles
• Experience with test‑driven development (TDD) and automated testing frameworks and modern API design patterns