- Design, develop, test, and optimize prompts for Large Language Models (LLMs).

- Collaborate with cross-functional teams including AI, Product, Engineering, and Data Science to deliver Generative AI solutions.

- Analyze model outputs and iteratively refine prompts to improve response quality, accuracy, and consistency.

- Experiment with prompt engineering techniques such as few-shot prompting, chain-of-thought prompting, and structured prompting.

- Develop reusable prompt templates, prompt libraries, and best practices.

- Work with AI playgrounds and evaluation tools to validate prompt effectiveness.

- Troubleshoot prompt performance issues and recommend improvements.

- Participate in prompt reviews, knowledge sharing, and documentation.

- Stay updated with the latest advancements in Generative AI, LLMs, and prompt engineering methodologies.

- Contribute to the continuous improvement of AI model performance and user experience.

Required Skills :

- 3 - 6 years of software engineering, AI/ML, NLP, or Prompt Engineering experience.

- Hands-on experience in Prompt Engineering for Large Language Models.

- Strong understanding of Natural Language Processing (NLP) concepts and techniques.

- Experience working with OpenAI GPT, Claude, Gemini, Llama, or similar LLMs.

- Proficiency in Python and scripting for AI applications.

- Experience with prompt testing, evaluation, and optimization.

- Familiarity with AI playgrounds and prompt experimentation environments.

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration abilities.

Good to Have :

- Experience with LangChain, LangGraph, LlamaIndex, DSPy, or Semantic Kernel.

- Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.

- Understanding of AI safety, prompt guardrails, and hallucination mitigation.

- Exposure to cloud AI services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.

- Experience building AI assistants, chatbots, or enterprise Generative AI applications.