GenAI & Agentic AI Engineer - Full time only

Role : GenAI & Agentic AI Engineer (4 openings)

Location : Whippany, NJ 07981 (Hybrid)

Full time

Experience Required: 5+ years in AI/ML

GenAI Experience: Minimum 2 years (hands‑on)

Agentic AI Experience: Minimum 6 months (CrewAI / AutoGen / LangGraph / LangChain Agents)

Role Summary

We are seeking a skilled GenAI & Agentic AI Engineer with strong experience in building end‑to‑end AI/ML solutions, Generative AI applications, and agent‑based automation workflows. The ideal candidate will have a solid background in machine learning along with hands‑on expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.

Key Responsibilities • 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 embedding‑based retrieval systems. • Build scalable AI services using Python, FastAPI/Flask, and cloud platforms (Azure/AWS/GCP). • Collaborate with cross‑functional teams to define use cases and convert them into production‑ready GenAI solutions. • Implement hallucination reduction, prompt‑engineering 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.

Required Skills & Experience • 5+ years of experience in AI/ML, including model development, data preprocessing, EDA, training, and evaluation. • 2+ years of hands‑on experience in Generative AI (LLMs, embeddings, RAG, LLM‑based apps). • 6+ months of hands‑on experience with Agentic AI frameworks (CrewAI / AutoGen / LangGraph / LangChain Agents). • Strong proficiency in Python and ML libraries (Scikit‑learn, Pandas, NumPy). • Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering. • Familiarity with building scalable APIs using FastAPI, Flask, or Django. • Hands‑on 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.