Experienced Prompt Engineer

Job Overview

We are seeking an experienced Prompt Engineer to design, optimize, and maintain prompts for Large Language Models (LLMs) and AI-driven applications. The role involves improving AI output quality, building prompt frameworks, and collaborating with engineering teams to develop scalable AI solutions. The ideal candidate has hands-on experience with LLMs, prompt optimization, and AI system design.

Key Responsibilities

• Design, develop, and optimize prompts for Large Language Models (LLMs) to improve accuracy, consistency, and reliability.
• Develop structured prompts and prompt templates for various AI use cases such as chatbots, document processing, data extraction, summarization, and automation.
• Perform prompt experimentation, A/B testing, and evaluation to improve AI performance.
• Collaborate with AI engineers, backend developers, and product teams to integrate prompt workflows into applications.
• Build and maintain prompt libraries and prompt pipelines.
• Implement techniques such as few-shot prompting, chain-of-thought reasoning, role prompting, and structured prompting.
• Reduce hallucinations and improve response quality through prompt optimization and validation strategies.
• Work with Retrieval Augmented Generation (RAG) pipelines and knowledge retrieval systems.
• Monitor model outputs and continuously refine prompts based on performance metrics.
• Document prompt strategies, experiments, and best practices.

Required Skills & Qualifications

• 3+ years of experience working with Generative AI, LLMs, or NLP systems.
• Strong expertise in Prompt Engineering techniques.
• Experience working with LLM APIs and AI platforms.
• Programming experience in Python, JavaScript, or similar languages.
• Strong understanding of LLM behavior, token limits, and prompt optimization.
• Experience evaluating AI outputs and improving response quality.
• Excellent analytical and problem-solving skills.

Preferred Qualifications

• Experience building RAG (Retrieval Augmented Generation) systems.
• Familiarity with vector databases (FAISS, Pinecone, Weaviate, etc.).
• Experience with LLM frameworks such as LangChain or LlamaIndex.
• Experience building AI-powered chatbots, assistants, or document processing systems.
• Understanding of LLM Ops, evaluation frameworks, and prompt testing.
• Knowledge of NLP and machine learning fundamentals.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field, or equivalent practical experience.