Prompt Engineer

Position Summary

The Prompt Engineer plays a key role in designing, optimizing, and managing interactions with large language models (LLMs) and generative AI systems. This role requires a mix of creativity, analytical thinking, and technical expertise to craft effective prompts, improve response quality, and integrate AI-driven workflows into business or technical operations.

Key Responsibilities

• Develop and refine effective prompts to achieve desired outputs from LLMs across various use cases (e.g., content generation, summarization, classification, automation).
• Experiment with prompt phrasing, context structuring, and parameter tuning to enhance accuracy, reliability, and tone of AI responses.
• Maintain a prompt library with tested and validated templates for reuse across teams.
• Evaluate model behaviour and performance across different prompt designs and model versions.
• Identify bias, inconsistencies, or hallucinations in outputs and adjust prompts or context data accordingly.
• Work with different team members to integrate prompt logic into applications and automation systems.
• Translate user or business requirements into structured prompt frameworks.
• Contribute to documentation, training materials, and playbooks for AI prompt usage.
• Stay up-to-date with advances in LLMs, generative AI, and prompt engineering best practices.
• Experiment with tools like LangChain, LlamaIndex, and Retrieval-Augmented Generation (RAG) frameworks.
• Explore prompt-based automation and multi-model orchestration opportunities.

Basic Qualifications

• Bachelor’s degree in Computer Science, Linguistics, Data Science, or related field (Master’s preferred).
• 2–5 years of experience working with AI/ML, NLP models, or automation systems.
• Strong command of English language and prompt composition techniques.
• Familiarity with LLM APIs (OpenAI, Anthropic, Google Vertex, Azure OpenAI, etc.).
• Scripting skills (Python, JavaScript, or similar) for prompt automation and API integration.
• Understanding of data privacy, bias mitigation, and ethical AI considerations.

Preferred Qualifications

• Addon Experience with LangChain, LlamaIndex, or RAG pipelines.
• Exposure to vector databases (Pinecone, Weaviate, FAISS).
• Knowledge of Chatbot frameworks, API development, or automation platforms.
• Basic understanding of fine-tuning and embedding models.