Prompt Engineer

Qode • Mahwah, NJ

6d

About The Position

We are seeking a highly creative and technically strong Prompt Engineer to design, optimize, and scale LLM-driven solutions within an Agentic POD architecture. The ideal candidate will have hands-on experience in LLM optimization (Gemini, Claude, Copilot), prompt engineering patterns, and Retrieval-Augmented Generation (RAG), along with a focus on improving engineering throughput and automation.

Requirements

• Strong understanding of LLMs and prompt engineering techniques
• Hands-on experience with LLM optimization (Gemini, Claude, Copilot, OpenAI models, etc.)
• Expertise in prompt patterns:
• Few-shot / zero-shot prompting
• Chain-of-thought reasoning
• ReAct / tool-based prompting
• Experience with RAG architectures (retrievers, embeddings, vector databases)
• Ability to design scalable prompt templates and reusable frameworks
• Strong analytical skills for evaluating and improving model outputs
• Familiarity with Python for prototyping and integration
• Overall 4 + years with 2-7 years of relevant work experience in Agentic AI Development
• B.Tech., M.Tech. or MCA degree from a reputed university

Nice To Haves

• Experience with LangChain / LangGraph / AutoGen
• Familiarity with vector databases (FAISS, Pinecone, Weaviate)
• Knowledge of cloud platforms (GCP preferred – Vertex AI, AI Studio)
• Understanding of workflow orchestration (Airflow / Cloud Composer)

Responsibilities

• Design, develop, and optimize prompts and prompt chains for LLM-based applications
• Work within Agentic POD architectures to enable seamless interaction between AI agents
• Optimize performance of LLMs such as Gemini, Claude, GitHub Copilot, and other foundation models
• Develop and implement prompt patterns (few-shot, chain-of-thought, ReAct, tool-augmented prompting)
• Build and enhance RAG (Retrieval-Augmented Generation) pipelines for accurate and context-aware responses
• Create reusable prompt templates and frameworks for enterprise-scale applications
• Improve engineering throughput by leveraging AI-assisted development workflows
• Evaluate and fine-tune prompts using LLM evaluation frameworks and metrics (accuracy, latency, cost)
• Collaborate with AI engineers, data scientists, and product teams to deliver optimized solutions
• Ensure responsible AI practices, bias mitigation, and prompt safety controls
• Continuously experiment with new prompting techniques and LLM capabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees