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Closed on August 31, 2026.
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Job Description
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 LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, 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 TypeScript 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, GitHub, and Azure DevOps 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, TypeScript
- AI and ML tooling: OpenAI family, Azure OpenAI, Anthropic, Gemini; LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen; Retrieval-Augmented Generation; vector databases
- Cloud and containers: Azure, AWS, GCP, Docker, Kubernetes
- Version control and DevOps: Git, GitHub, Azure DevOps
- Testing and automation: Playwright automation, API testing, test automation frameworks, functional regression testing, CI/CD testing practices