An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
Whippany, NJ (Hybrid) Role Overview We are looking for a hands-on AI Engineer with strong practical experience in Python, TypeScript, LLMs, Agentic AI, and RAG-based applications . The ideal candidate should have experience designing, developing, and deploying enterprise-grade AI solutions and be comfortable working across the complete AI application lifecycle, from development to production deployment. Key Responsibilities Design and develop AI-powered applications using LLMs, Agentic AI frameworks, and RAG architectures . Build and deploy enterprise AI solutions for business use cases. Develop backend services and AI workflows using Python and TypeScript . Implement multi-agent workflows, orchestration patterns, and tool integrations. Create and optimize RAG pipelines, including document ingestion, vector databases, retrieval strategies, and prompt engineering. Evaluate LLM performance and implement monitoring, testing, and quality assessment frameworks. Build and maintain CI/CD pipelines using GitHub Actions . Support automated deployment, model lifecycle management, and production operations. Collaborate with architects, product owners, and business stakeholders to translate requirements into scalable AI solutions. Follow software engineering best practices, including code reviews, testing, security, and documentation. Mandatory Skills Strong hands-on experience in Python development. Good experience with TypeScript and modern application development. Practical experience with LLMs , prompt engineering, and AI application development. Hands-on knowledge of Agentic AI , multi-agent systems, and workflow orchestration. Experience building RAG (Retrieval-Augmented Generation) solutions. Strong understanding of GitHub Actions , CI/CD pipelines, and deployment automation. Experience with REST APIs, microservices, and enterprise application integration. Knowledge of LLM evaluation, testing, monitoring, and optimization techniques. Preferred Skills Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar . Exposure to vector databases such as Pinecone, Weaviate, FAISS, ChromaDB, or Azure AI Search . Experience with cloud platforms ( AWS, Azure, or Google Cloud Platform ). Understanding of MLOps concepts and AI solution deployment. Knowledge of containerization technologies such as Docker and Kubernetes . Required Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, or related field. Excellent communication and stakeholder management skills. Ability to work independently and collaboratively in agile teams. Strong problem-solving and analytical mindset. Nice to Have Experience with enterprise AI platforms and production AI deployments. Exposure to Responsible AI, AI governance, and security best practices. Experience with monitoring and observability tools for AI applications. This role is ideal for candidates who can combine software engineering expertise with practical GenAI, Agentic AI, and RAG implementation experience to deliver scalable enterprise AI solutions.
