Lead Software Engineer, Full Stack / React

JPMorgan Chase

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: Plano, TX
Posted: 42 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $207k

$187k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $192,050–$222,000.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Full Stack / React

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As a Lead Software Engineer - Full Stack / React within the Corporate Sector - Infrastructure Platforms - Data and Speciality Services team, you will serve as a core technical contributor in an agile environment. You will design, develop, and operate enterprise-scale infrastructure services while establishing AI-native engineering practices to improve code quality and delivery speed. Your daily responsibilities include writing production code, troubleshooting complex problems, leading communities of practice, and evaluating external vendor technologies. You will work with tools across the software development life cycle, focusing on automation, CI/CD, and application resiliency. Required skills include proficiency in languages such as Python, Go, Java, C++, or Rust, along with React for full-stack development. You will solve technical challenges within infrastructure domains like cloud, networking, compute, storage, security, or data infrastructure to ensure stable, scalable systems.

Skills

Python Go Java C++ Rust React Full Stack AI-assisted development CI/CD Agile Software Development Life Cycle System Design Automated Testing Security Application Resiliency

What you'll do

Design, develop, and troubleshoot creative software solutions for complex technical problems.
Establish and implement AI-native engineering practices across the entire software development life cycle.
Drive team adoption of enterprise-authorized AI tools to improve code quality and delivery speed.
Own the design, delivery, and operation of enterprise-scale infrastructure services from architecture through production.
Write and review high-quality production code while maintaining a hands-on engineering approach.
Identify and automate the remediation of recurring issues to improve system operational stability.
Lead evaluation sessions with vendors and internal teams to assess architectural designs and technical feasibility.
Lead communities of practice to promote the use of leading-edge technologies across the organization.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on practical experience in system design, application development, testing, and operational stability.
Demonstrated experience leading the use of approved AI-assisted software development tools with validation standards for correctness and security.
Strong understanding of responsible AI use in engineering workflows including data sensitivity and secure handling of inputs/outputs.
Advanced hands-on experience engineering production code in one or more industry-standard languages (e.g., Python, Go, Java, C++, Rust).
Deep experience building and operating systems in at least one infrastructure domain such as cloud, networking, compute, storage, security, or data.
Experience running production systems at scale, including on-call ownership, incident response, and designing for reliability.
Proficiency in automation, continuous delivery methods, agile methodologies (CI/CD), and the full Software Development Life Cycle.
Experience across multiple infrastructure domains or programming languages (preferred).
Track record of reducing operational toil and cost through automation and better engineering (preferred).
Experience adopting AI-native engineering practices at team or organizational scale (preferred).
Prior experience in regulated or large-scale enterprise environments (preferred).
Experience with greenfield builds and establishing engineering culture (preferred).
Ability to influence engineering patterns beyond the immediate team (preferred).