Prompt Engineer - LLM

About the Role :

We are seeking a curious, creative, and technically strong Prompt Engineer to work on designing, testing, and optimizing natural language prompts that interface with Large Language Models (LLMs). Youll play a critical role in building intelligent, context-aware, and human-like AI applications across domains such as customer support, content generation, search, analysis, and automation.

This role sits at the intersection of AI research, UX design, and applied linguistics, and is ideal for candidates passionate about language, AI behavior, and emerging technologies.

Key Responsibilities :

• Craft, test, and refine prompts to achieve desired model behavior across tasks (e.g., Q&A, summarization, reasoning, extraction).
• Analyze LLM outputs to assess quality, consistency, accuracy, and hallucination rates.
• Collaborate with product managers, engineers, and data scientists to integrate prompts into live products.
• Develop evaluation frameworks and benchmarks for prompt effectiveness and performance.
• Explore prompt engineering strategies like few-shot learning, chain-of-thought (CoT), and retrieval-augmented generation (RAG).
• Conduct A / B testing and fine-tune prompts to optimize for KPIs such as response relevance, latency, and user satisfaction.
• Stay up to date on advancements in LLMs, prompt design, and generative AI Qualifications :
• Bachelors or Masters degree in Computer Science, Linguistics, Cognitive Science, AI, or a related field - or equivalent experience.
• 1-3 years of hands-on experience with LLMs (e.g., OpenAI GPT-4, Claude, Cohere, Mistral, etc.).
• Proficiency in prompt engineering best practices and experience designing prompts for real-world use cases.
• Basic coding skills (Python preferred) for testing and integrating prompt pipelines.
• Strong analytical and linguistic reasoning skills.
• Familiarity with APIs from OpenAI, Anthropic, Hugging Face, or similar Qualifications :
• Experience with tools like LangChain, LlamaIndex, or Semantic Kernel.
• Familiarity with RAG, embeddings, and vector databases (e.g., Pinecone, FAISS).
• Understanding of human-in-the-loop (HITL) and reinforcement learning from human feedback (RLHF).
• Experience working in AI-powered products, chatbots, or digital assistants.
• Background in creative writing, UX copywriting, or linguistics is a plus

(ref : hirist.tech)