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Senior Java Developer with Agentic AI (W2 Only)

Congensys Corp.Jersey City, NJ🇺🇸United StatesPosted 26 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Jersey City, NJ, United States
Posted
Yesterday
AWSSplunkJavaKafkaKubernetesLESS

Job Description

Hi

Hope you are Doing well,

 

Senior Java Developer with Agentic AI (less experience is also fine)

Locations: NYC NY/ Jersey City NJ

W2 Candidates Only locals/Near by Candidates  

$80 pr hr on W2

 

Skills required - Java, AWS preferred, Kubernetes, some streaming/Kafka, NOSQL, CI/CD, testing, alerts, and monitoring(Splunk/dynatrace). Must know AI for code optimization to accelerate development.

 

 

 

  • 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
  • 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.

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