Prompt Engineer

Job Responsibilities:

• Design, develop, and optimize prompts to improve the performance and accuracy of AI language models in various applications.
• Conduct research on prompt engineering techniques, including few-shot learning, chain-of-thought prompting, and reinforcement learning-based prompt tuning.
• Collaborate with data scientists, software engineers, and product teams to integrate prompt-based solutions into AI-driven products and services.
• Analyze model outputs, fine-tune prompts, and iterate based on evaluation metrics and user feedback.
• Develop automated tools and frameworks for testing and refining prompts to enhance model robustness and adaptability.
• Stay up to date with the latest advancements in LLMs, NLP, and AI prompting techniques to continuously enhance system performance.
• Document best practices, guidelines, and strategies for effective prompt engineering.
• Complete other tasks assigned by leadership related to AI prompt optimization and deployment.

Job Requirements:

• Bachelor’s degree or above in Computer Science, AI, NLP, or a related field.
• Strong understanding of LLMs (e.g., GPT, Claude, Gemini, Llama, Mistral) and experience with prompt engineering techniques.
• Hands-on experience in fine-tuning LLMs, using LoRA, RAG, or instruction tuning is a plus.
• Proficiency in Python and experience working with AI/ML frameworks such as Hugging Face, OpenAI API, LangChain, LlamaIndex, or similar tools.
• Strong analytical skills with the ability to assess model responses and refine prompts systematically.
• Familiarity with vector databases (e.g., FAISS, ChromaDB, Pinecone) and retrieval-augmented generation (RAG) methodologies is a plus.
• Experience in A/B testing, model evaluation, or reinforcement learning is a plus.
• Strong communication and teamwork skills to collaborate effectively with cross-functional teams.