Role Description

Technical > Prompt Engineer

Salary National Average

Low Medium High
1.0000 1.0000 1.0000

Supply and Demand

Candidate Supply: 0 Job Openings: 0

0 50 100

More Difficult Less Difficult

Salary Variance

Enter City, State to view local salaries and candidate demand.

Short Description:

A Prompt Engineer is responsible for designing, testing, and refining prompts that optimize the performance and accuracy of large language models and other AI systems. They analyze model outputs, identify areas for improvement, and develop prompt frameworks that enhance relevance, creativity, and reliability. The role involves collaborating with data scientists, product teams, and domain experts to align AI behavior with business or user goals. Prompt Engineers bridge the gap between human intent and machine understanding to deliver high-quality AI-driven results. Strong analytical thinking, language proficiency, and familiarity with AI model behavior are essential for success in this role.

Duties / Responsibilities:

  • Design, develop, and refine prompts to optimize the performance of large language models (LLMs) across diverse tasks and applications
  • Collaborate with data scientists, software engineers, and product managers to align prompt design with project goals and business requirements
  • Conduct experiments to evaluate prompt effectiveness, analyze model outputs, and iterate based on quantitative and qualitative feedback
  • Develop prompt templates and frameworks that can be reused or adapted for different domains, use cases, and model architectures
  • Research and document best practices in prompt engineering, including token efficiency, bias mitigation, and response accuracy
  • Collaborate with AI researchers to improve model interpretability, consistency, and reliability through advanced prompt strategies
  • Integrate prompt workflows into production systems, APIs, or user-facing tools to automate or scale AI-driven solutions
  • Monitor model behavior in real-world scenarios and adjust prompts to improve contextual relevance and performance stability
  • Support the creation of evaluation datasets and benchmarks to test model accuracy, safety, and ethical compliance
  • Communicate findings and methodologies through detailed documentation, internal training, or technical presentations

Skills / Requirements / Qualifications

  • Education: Bachelor’s or Master’s degree in computer science, computational linguistics, data science, or a related technical field
  • Experience: 2–5 years of experience in natural language processing (NLP), AI model tuning, or data-driven product development
  • Technical Knowledge: Strong understanding of LLM architectures, tokenization, and NLP concepts such as embeddings, context windows, and fine-tuning
  • Programming Skills: Proficiency in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or LangChain
  • Analytical Skills: Ability to design and interpret experiments, analyze model behavior, and optimize prompts for measurable performance gains
  • Communication: Clear written and verbal communication skills for documenting prompt logic and collaborating across technical and non-technical teams
  • Creativity & Problem-Solving: Innovative mindset for crafting effective prompts that balance precision, tone, and contextual understanding
  • Ethical Awareness: Understanding of AI safety, bias mitigation, and responsible use of generative models in real-world applications

Job Zones

  • Title: Job Zone Five Extensive Preparation Needed
  • Education: Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree).
  • Related Experience: Extensive skills, knowledge, and experience are needed for these occupations. Many require more than five years of experience. 
  • Job Training: Employees may need some on-the-job training, but most of these occupations assume that the person will already have the required skills, knowledge, work-related experience, or training.
  • Job Zone Examples: These occupations often involve coordinating, training, supervising, or managing the activities of others to accomplish goals. Very advanced communication and organizational skills are required. 
  • Specific Vocational Preparation in years: 4-7 years preparation (8.0 and above)

Share Role Details

Return to job listings