Prompt Engineer

• Bachelors degree in Computer Science, Linguistics, Psychology, Communications, or a related field.
  
• Minimum of 2-4 years of experience working with or around Large Language Models or similar Generative AI technologies.
  
• Strong understanding of the capabilities and limitations of current LLMs.
  
• Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly.
  
• Creative thinking and problem-solving skills to devise effective prompting strategies.
  
• Ability to analyze and interpret the outputs of AI models.
  
• Familiarity with different prompting techniques and their applications.
  
• Strong attention to detail and a methodical approach to experimentation and optimization.
  
• Proficiency in using relevant tools and platforms for interacting with LLMs.

Key Responsibilities:

• Design, develop, and test a variety of prompts for different Generative AI models to achieve specific goals and outcomes.
  
• Iterate on prompts based on model outputs, user feedback, and performance metrics to continuously improve results.
  
• Develop and maintain a library of effective prompts and prompt templates for various use cases.
  
• Collaborate with AI Engineers, Data Scientists, and Product Managers to understand requirements and translate them into effective prompting strategies.
  
• Analyze the behavior and outputs of LLMs to identify patterns and areas for prompt optimization.
  
• Stay up-to-date with the latest advancements in prompt engineering techniques and best practices.
  
• Document prompt designs, testing results, and best practices.
  
• Contribute to the development of tools and processes to streamline prompt creation and management.
  
• Experiment with different prompting techniques, such as few-shot learning, chain-of-thought prompting, and retrieval-augmented generation.
  
• Evaluate the impact of different prompting strategies on the accuracy, coherence, and relevance of model outputs.

What will excite us:

• Experience in developing applications or features that utilize LLMs.
  
• Familiarity with AI ethics and responsible AI development practices.
  
• Experience with data analysis and performance evaluation of AI models.
  
• Understanding of software development workflows and version control.
  
• Experience working in an agile development environment.