Prompt Engineer

We are seeking a skilled and passionate Prompt Engineer with expertise in Prompt Engineering and LLM-based application development. As a Prompt Engineer, you will be responsible for designing, developing, and scaling GenAI-powered applications using cutting-edge technologies in AI, full-stack development, and cloud computing. Your key responsibilities will include designing and developing AI applications utilizing Large Language Models (LLMs) such as GPT-4, Claude, or LLaMA. You will be tasked with writing, optimizing, and evaluating prompts for various tasks and use cases. Proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies is essential for this role. Additionally, you will be expected to build responsive frontend interfaces using frameworks like React.js, Vue.js, or similar. Integration with AI APIs such as OpenAI, Azure OpenAI, Cohere, etc., and working with frameworks like LangChain, LlamaIndex, and RAG pipelines will be part of your daily tasks. Implementing vector databases like Pinecone, Weaviate, and FAISS for knowledge retrieval is also crucial. Collaboration with cross-functional teams for system integration and deployment to ensure best practices in coding, testing, DevOps, and cloud deployment is a key aspect of this role. The ideal candidate should possess proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies and have experience with AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face. Hands-on experience with Prompt Engineering for Large Language Models (LLMs) such as GPT, Claude, LLaMA, etc., and knowledge of RAG, LangChain, or LlamaIndex are highly desired. Familiarity with AI APIs like OpenAI, Azure OpenAI, and backend development using FastAPI, Flask, or Express is required. Experience in frontend development using React or Vue.js, familiarity with CI/CD, Docker, and cloud platforms (AWS, Azure, GCP) are essential skills for this role. Preferred skills include experience with LangChain, LlamaIndex, or similar frameworks, familiarity with tools like Hugging Face, OpenAI Playground, Azure OpenAI Studio, knowledge of MLOps tools, and data pipelines, and understanding of prompt tuning and fine-tuning LLMs.,