Java Engineer

GLOBAL TRANSGENDER SAFETY TASKS FORCE. USA INC

United States

4 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Automation of Tests Microsoft Azure Software Bug Management Continuous Integration Java Platform Enterprise Edition (J2EE) Identity and Access Management Java Development Kit Key Management Regression Analysis

+15 more

Systems Development Life Cycle Release Management Secure Coding Software Engineering Software Vulnerability Management Web Application Frameworks Google Cloud Cloud Platform System Delivery Pipeline IT Architecture Containerization AngularJS Enterprise Integration Restful APIs Software Version Control

Requirements

Senior-level experience designing, building, testing, deploying, and supporting enterprise Java applications.
Hands-on experience completing major Java/JDK upgrades or comparable platform modernization efforts.
Strong understanding of dependency compatibility, build pipelines, automated testing, regression analysis, secure coding, and release management.
Experience with Angular or another modern front-end framework and the ability to troubleshoot integrated full-stack applications.
Strong systems-engineering mindset and understanding of the complete software delivery lifecycle.
Experience with REST APIs, service integration, source control, CI/CD, observability, defect management, and controlled production change.
Understanding of authentication, authorization, entitlement models, secrets management, and security-first application design.
Ability to work independently in an ambiguous environment, develop structure, and drive assignments to measurable completion.
Clear written and verbal communication, effective collaboration, and a proactive, accountable work style., * Experience designing, building, securing, or operating MCP servers or similar AI-to-enterprise integration layers.
Understanding of enterprise AI architecture, knowledge integration, retrieval patterns, evaluation, guardrails, and AI-assisted development.
Experience with public cloud platforms, particularly Azure; AWS or Google Cloud Platform exposure is also valuable.
Experience in highly regulated financial-services environments.
Knowledge of identity and access management, policy services, segregation of duties, secrets rotation, or credentials migration.
Experience with container platforms and secure application deployment.
Background in vulnerability remediation, audit evidence, and security/compliance controls.