We are looking for a Prompt Engineer with hands-on experience in working with Large Language Models (LLMs) to contribute to the development of the natural language generation layer in an intelligent search engine platform. The goal of the project is to transform structured data outputs (e.g., GraphQL query results) into clear, human-readable responses using advanced LLM prompting techniques. You will play a key role in designing prompt strategies, optimizing model behavior, and shaping user-agent interactions to ensure data-driven insights are delivered with high accuracy and linguistic quality.
responsibilities :
Design, implement, and fine-tune prompts and workflows for LLMs.
Collaborate with data engineers and product teams to understand structured outputs (e.g., GraphQL results) and convert them into high-quality natural language responses.
Optimize generative AI outputs for relevance, precision, and readability.
Prototype and iterate on agent-based LLM interactions to enhance search engine capabilities.
Analyze model outputs and conduct performance evaluations to ensure consistent delivery of accurate and user-friendly responses.
Contribute to best practices and documentation related to prompt engineering and generative AI workflows.
requirements-expected :
Proven experience with Prompt Engineering and working with LLMs (e.g., OpenAI, Anthropic, Cohere, etc.).
Strong background in data analysis, especially in interpreting structured query outputs.
Hands-on experience with Generative AI models in production or research environments.
Proficiency in designing prompt-based systems for data-to-text generation.
Understanding of model behavior tuning, including temperature, top-k/top-p sampling, and few-shot/zero-shot prompting techniques.
Experience with agent workflow design and orchestration of multi-step model interactions is a strong plus.
Excellent communication skills and ability to work effectively in a remote, cross-functional team environment.
