Senior Full-Stack Engineer: Java/Python/React

Socket.dev; New Jersey; On-site; USD 130,000 - 190,000; Full time

Benefits offered by this job

Comprehensive health care coverage

On-site health and wellness centers

Retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching and more

Job summary

JPMorgan Chase is seeking a seasoned Software Engineer III to join the Global Technology Vendor Management Engineering Team. The role focuses on designing and delivering secure, scalable software using Java or Python and modern front-end stacks like React, while leveraging AI coding assist tools.

Responsibilities include building high-quality production code, producing architecture artifacts, and driving improvements from data analyses across large datasets.

Qualifications

• 3+ years of experience in system design, development and stability.
• Proficiency in Java or Python and modern front-end stacks.
• Experience in a large corporate environment and SDLC knowledge.
• Experience with AI-assisted development tools is a plus.

Responsibilities

• Executes software solutions, design, development, and troubleshooting.
• Produces secure, high-quality production code and maintains algorithms.
• Leverages AI coding tools to improve code quality and speed under peer review.
• Applies SDLC tools and architectures to enhance automation and value.
• Creates architecture artifacts and visualizations from large data sets.
• Investigates and resolves issues; drives improvements in code hygiene.

Skills

Java

Python

React

Agile methodologies

Tools

HTML5

CSS

Sass

LESS

Job description

JPMorgan Chase is seeking a seasoned Software Engineer III to join the Global Technology Vendor Management Engineering Team. The role focuses on designing and delivering secure, scalable software using Java or Python and modern front-end stacks like React, while leveraging AI coding assist tools.

Responsibilities include building high-quality production code, producing architecture artifacts, and driving improvements from data analyses across large datasets.