Drimva

JPMorgan Chase

Java, Linux Lead Software Engineer – Security & Privileged Access

$157K–$215K

Jersey City, NJ · Full-time · Posted Sep 25, 2026

Experience
5+ years applied experience.
Education
Formal training or certification on software engineering concepts.

About the job

Leads software engineering for security and privileged access in the Corporate Technology Identity and Access Management team, building and maintaining secure, stable, scalable technology and promoting AI-assisted engineering practices.

What you'll do

  • Designs, develops, tests, troubleshoots, reviews, and debugs production software; improves application stability through automation.
  • Leads technical and architectural evaluations and promotes adoption of leading-edge technologies across engineering teams.
  • Drives responsible team adoption of authorized AI-assisted engineering tools, with validation standards for security, correctness, and performance.

What they ask for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Hands-on experience delivering system design, application development, testing, and operational stability; advanced Java and Shell Scripting skills, with strong OOP and design-pattern knowledge.
  • Experience with Linux systems, automation and continuous delivery, and authentication, authorization, encryption, RBAC, and ABAC.
  • Experience with agile methods, CI/CD, application resiliency and security across the SDLC; cloud-native technologies, real-time messaging, SQL and NoSQL databases, and leading responsible use of approved AI-assisted development tools.

Nice to have

  • In-depth knowledge of financial services and its IT systems; practical knowledge of cloud-native platforms and solutions.
  • Terraform or infrastructure as code, infrastructure (OS, network, storage), SRE monitoring and observability, or Python.

Pay

$156,750.00-$215,000.00 USD base salary

Tools

Java, Shell Scripting, Linux, CI/CD, SQL, NoSQL, Terraform, Python

AI focus

Leads adoption of authorized AI-assisted coding, code review/refactoring, test acceleration, troubleshooting, and incident/root-cause analysis. Establishes validation practices and coaches engineers on secure, responsible use, including data sensitivity and safe handling of inputs and outputs.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 4, 2026 (UTC)