GenAI & Agentic AI Engineer

Role: GenAI & Agentic AI Engineer Location: Whippany, NJ (Hybrid) Hire Type: FTE

*Must be legally authorized to work in US without need for employer sponsorship now or at any time in the future.

About Position: We are looking for a skilled GenAI & Agentic AI Engineer with strong experience in building endtoend AI/ML solutions, Generative AI applications, and agentbased automation workflows. The ideal candidate will have a solid background in machine learning along with handson expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.

What You'll Do: • Build and deploy GenAI applications using LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.). • Develop Agentic AI workflows using frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents. • Design and implement RAG pipelines, vector search solutions, and embeddingbased retrieval systems. • Build scalable AI services using Python, FastAPI/Flask, and cloud platforms (Azure/AWS/GCP). • Collaborate with crossfunctional teams to define use cases and convert them into productionready GenAI solutions. • Implement hallucination reduction, promptengineering strategies, and model evaluation methods. • Integrate LLMs with enterprise applications, APIs, and automation workflows. • Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search. • Monitor, evaluate, and optimize GenAI models for accuracy, performance, and cost. Expertise You'll Bring: • 5+ years of experience in AI/ML, including model development, data preprocessing, EDA, training, and evaluation. • 2+ years of handson experience in Generative AI (LLMs, embeddings, RAG, LLMbased apps). • 6+ months of handson experience with Agentic AI frameworks (CrewAI / AutoGen / LangGraph / LangChain Agents). • Strong proficiency in Python and ML libraries (Scikitlearn, Pandas, NumPy). • Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering. • Familiarity with building scalable APIs using FastAPI, Flask, or Django. • Handson knowledge of cloud services (Azure/AWS/GCP) for AI deployment. • Strong understanding of REST APIs, microservices, and integration patterns. • Experience with Git, CI/CD, Docker, and model deployment best practices.

Flexible work from home options available. Employment Type: FULL_TIME