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AI Engineer

Job in Newark, Essex County, New Jersey, 07175, USA
Listing for: Coforge Ltd.
Full Time position
Listed on 2026-08-07
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Cloud Engineer - Software, Backend Developer, DevOps
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below

An on-site AI Engineer role based in New Jersey, focused on designing, developing, and deploying AI-powered applications and agentic workflows in production using LLMs, Retrieval-Augmented Generation, and prompt engineering. Collaboration spans AI architecture, development (Java and frontend), and QA (Playwright) to deliver enterprise-grade AI solutions.

Responsibilities
  • Design, develop, and deploy AI powered applications leveraging contemporary LLM technologies.
  • Create and implement agentic workflows using AI agents, orchestration frameworks, and automation platforms.
  • Build Retrieval-Augmented Generation pipelines employing vector databases and enterprise knowledge sources.
  • Conduct prompt engineering, optimization, and model evaluation to improve AI accuracy and reliability.
  • Fine-tune foundation models when needed to satisfy business requirements.
  • Integrate AI capabilities into existing enterprise applications and platforms.
  • Monitor, optimize, and sustain AI systems in production environments.
  • Develop backend services and RESTful APIs using Java frameworks.
  • Create responsive, scalable frontend applications to deliver AI driven user experiences.
  • Collaborate with architects, product owners, and business stakeholders to translate requirements into technical solutions.
  • Implement integrations with internal and external systems via APIs and microservices.
  • Develop automated testing strategies for AI-enabled applications.
  • Design and execute UI and API automation using Playwright.
  • Validate AI outputs through functional, regression, and performance testing.
  • Establish testing frameworks and quality gates for AI solutions deployed in production.
  • Ensure security, performance, and reliability standards are met.
  • Work closely with AI Architects, Data Scientists, Product Teams, and Business SMEs.
  • Stay current with emerging AI technologies, frameworks, and industry best practices.
  • Contribute to AI governance, responsible AI practices, and solution documentation.
Requirements
  • Prompt engineering proficiency.
  • Experience with Large Language Models including OpenAI, Azure OpenAI, Anthropic, Gemini, and others.
  • Proficiency with agentic AI frameworks.
  • Expertise in Retrieval-Augmented Generation (RAG).
  • Knowledge of vector databases.
  • Experience with model evaluation and optimization.
  • Understanding of fine-tuning concepts.
  • AI application development experience.
  • Experience with AI orchestration frameworks such as Lang Chain, Lang Graph, Semantic Kernel, CrewAI, Auto Gen, etc.
  • Java 8, 11, or 17+ development experience.
  • Spring Boot expertise.
  • REST APIs and microservices architecture experience.
  • API integration skills.
  • Frontend experience with React.js, Angular, or other modern JavaScript frameworks.
  • HTML5, CSS3, JavaScript, and Type Script proficiency.
  • Playwright automation experience.
  • API testing experience.
  • Test automation framework design experience.
  • Functional regression testing experience.
  • CI/CD testing practices knowledge.
  • Experience with Azure, AWS, or GCP clouds.
  • Docker and Kubernetes experience.
  • CI/CD pipelines experience.
  • Git, Git Hub, and Azure Dev Ops familiarity.
Technologies
  • Core programming and backend:
    Java (8/11/17+), Spring Boot, REST APIs, microservices
  • Frontend stack:
    React.js, Angular, modern JavaScript frameworks, HTML5, CSS3, JavaScript, Type Script
  • AI and ML tooling:
    OpenAI family, Azure OpenAI, Anthropic, Gemini;
    Lang Chain, Lang Graph, Semantic Kernel, CrewAI, Auto Gen;
    Retrieval-Augmented Generation; vector databases
  • Cloud and containers:
    Azure, AWS, GCP, Docker, Kubernetes
  • Version control and Dev Ops:
    Git, Git Hub, Azure Dev Ops
  • Testing and automation:
    Playwright automation, API testing, test automation frameworks, functional regression testing, CI/CD testing practices
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