THE ROLE: We have two positions open. Improve the efficiency of large language models and generative AI systems by crafting, optimizing, and managing prompts that drive accurate, reliable, and valuable AI outputs. This role exists to bridge human intent and AI capability, crafting prompts that unlock the full potential of AI models while ensuring outputs meet quality, safety, and business requirements. The AI Prompt Engineer combines technical understanding of AI systems with creative problem-solving to build robust prompt frameworks that enable AI-powered solutions. HOW YOU WOULD CONTRIBUTE: Design and optimize prompts for large language models (LLMs) and generative AI systems to achieve specific business outcomes Develop timely engineering frameworks and guidelines for different AI use cases and applications Test and iterate on prompts systematically to improve accuracy, consistency, and output quality Build prompt templates and libraries that enable reusable, scalable AI solutions across the organization Implement prompt chaining and multi-step reasoning approaches for complex AI tasks Design and optimize retrieval-augmented generation (RAG) systems combining prompts with knowledge bases Evaluate AI model outputs against quality criteria and implement improvement strategies Conduct prompt injection testing and implement safeguards against adversarial inputs Collaborate with developers to integrate prompts into applications and workflows Monitor production prompt performance and implement versioning and A/B testing strategies Document prompt patterns, techniques, and findings for team knowledge sharing Stay current with LLM capabilities, limitations, and best practices across different models Provide guidance on prompt engineering to data scientists, developers, and business users Analyze failure modes and edge cases, developing strategies to improve robustness Implement ethical AI practices ensuring prompts produce fair, unbiased, and safe outputs Make decisions on prompt strategies, model selection, and optimization approaches for AI applications
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees