Looking for Prompt Engineer || Jersey City, NJ / New York, NY || Fulltime

Hi, Hope you are doing well. We do have a position for Prompt Engineer with our client. Please find the details below and if interested please send me your updated word format resume.

Tittle:

Prompt Engineer Location:

Jersey City, NJ /

New York, NY Duration:

Fulltime Experience :

4-6

Years Must Have Technical/Functional Skills:

We are looking for experienced Prompt Engineers with strong hands-on expertise in Large Language Models (LLMs) to design, optimize, and operationalize high quality prompts for enterprise-grade GenAI solutions. The role demands deep understanding of model behaviour, prompt patterns, and real-world deployment in regulated environments. 4 7+ years overall experience, with 2 3+ years hands-on Prompt Engineering / GenAI work. Strong experience with LLMs (GPT 4 / GPT 4o / Gemini / Claude / LLaMA or equivalent). Hands-on knowledge of RAG frameworks, embeddings, vector databases, and semantic search. Experience with Azure OpenAI / OpenAI APIs / Google Vertex AI / Hugging Face. Strong NLP fundamentals and ability to interpret LLM behaviour. Programming experience in Python (Fast API / Flask exposure preferred). Experience using LangChain / LlamaIndex or similar orchestration frameworks. Strong analytical skills to evaluate and improve model output quality.

Roles & Responsibilities:

Design, test, and optimize advanced prompts (zero-shot, few-shot, chain-of-thought, tool calling, RAG-based prompts) for LLM-driven applications. Analyse model outputs and continuously refine prompts to ensure accuracy, consistency, and business relevance. Collaborate with Data Scientists, ML Engineers, and Product teams to integrate prompts into end-to-end AI workflows. Support RAG architectures by crafting effective prompts leveraging vector search, embeddings, and enterprise knowledge sources Implement guardrails, validation strategies, and hallucination mitigation techniques. Fine tune prompt strategies based on domain-specific use cases (knowledge extraction, summarization, classification, Q&A, reasoning tasks). Document prompt patterns, best practices, and reusable templates for enterprise adoption. Support client demos, POCs, and pilot rollouts of GenAI solutions. Bhakti Chaudhari