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Java AIML Full Stack Engineer

Job in Hanover Township, Morris County, New Jersey, USA
Listing for: Precision Technologies
Full Time position
Listed on 2026-02-21
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Title:
Java AIML Full Stack Engineer (AI/ML Integrated)

Location:
Whippany, NJ (Onsite)

Experience: 9+

Full Time

Role Purpose

To design, develop, and maintain complex, end-to-end software solutions that integrate Artificial Intelligence and Machine Learning capabilities. You will build responsive user interfaces, scalable backend microservices, and ensure seamless integration with ML models to drive automation and data-driven decision‑making across client’s financial platforms.

Key Responsibilities
  • Full Stack Development: Build and maintain scalable web applications using React.js or Angular for the frontend and Java (Spring Boot), Python (Fast API/Django), or Node.js for the backend.
  • AI/ML Integration: Work closely with Data Scientists to deploy and integrate ML models (including LLMs, Predictive Models, and NLP) into production environments via RESTful APIs.
  • Generative AI & LLMs: Develop applications leveraging Gen AI, RAG (Retrieval-Augmented Generation) architectures, and Agentic frameworks (e.g., Lang Chain).
  • Database Management: Design and optimize schemas for both SQL (Oracle, Postgre

    SQL) and No

    SQL (Mongo

    DB, Cassandra) databases.
  • Cloud & Dev Ops: Deploy applications using AWS or Azure services. Build and maintain CI/CD pipelines using Jenkins, Docker, and Kubernetes (Open Shift).
  • Technical Excellence: Adhere to Test-Driven Development (TDD) and Behavior-Driven Development (BDD) practices to ensure code quality and security.
Skills & Qualifications

Backend: Java 17+ (Spring Boot, Spring AI), Python, Microservices architecture

AI/ML

Competency:

Understanding of ML life cycles, experience with PyTorch or Tensor Flow, and exposure to Gen AI/LLM platforms

Soft Skills: Strong problem-solving, collaboration in Agile squads

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