Prompt Engineer – Gen AI at SRS Distribution Inc.

Posted on (3 months ago)

Location: McKinney, TX, United States

Industry: Wholesale Building Materials

Job Type: full-time

Experience Level: entry-level

Remote: on-site

Job Description

We are looking for a Prompt Engineer to join our team and ensure the creation of effective and engaging interfaces for our AI-generated content solutions. This is an exciting opportunity at SRS Distribution, and you will be at the forefront of the Gen AI initiatives at SRS to drive the user experience and practical capabilities for our various teams!

Responsibilities

  • Conduct extensive research to identify and curate relevant data sources for prompt development.
  • Analyze, design, develop, and refine diverse prompts tailored to specific AI tasks and applications.
  • Ensure the prompts are intuitive for a productive conversation to elicit desired responses and achieve outcomes.
  • Optimize AI prompt generation process to enhance overall system performance.
  • Integrate prompt designs into natural language processing (NLP) models.
  • Ensure seamless integration of prompt engineering strategies into existing AI systems.
  • Conduct thorough evaluations of prompt effectiveness through data analysis and user feedback.
  • Iterate on prompt designs based on performance metrics, aiming for continual improvement in conversational capabilities.
  • Develop and maintain quantitative key performance indicators to evaluate the effectiveness of AI prompts. Draft and distribute reports on prompt performance to identify areas for improvement.
  • Work closely with UX/UI designers, product managers, and other stakeholders to align prompt design with user experience goals and overall project objectives.
  • Stay ahead of AI advancements, natural language processing, and machine learning to apply to our business objectives proactively.
  • Document prompt design strategies, methodologies, and outcomes for internal reference and knowledge sharing.
  • Communicate effectively with team members and stakeholders, presenting findings and recommendations related to prompt engineering.
  • Collaborate with business stakeholders, product team, and developers to understand use cases, project requirements, and objectives.
  • Collaborate with content creators, product teams, and data scientists to ensure prompt accuracy and alignment with company goals and user needs.

Requirements

  • Bachelor’s degree, preferred in computer science, engineering, or a related field. Master's degree preferred.
  • 3+ years of experience in software development with Proficiency in programming languages such as Python, Java, or similar is essential for implementing and integrating prompt engineering solutions into existing AI systems.
  • 2+ years developing applications using AI, natural language processing, and speech recognition.
  • Skills in data analysis and statistical methods are valuable for assessing the performance of prompts, analyzing user interactions, and making informed adjustments to enhance the overall system.
  • Comprehensive understanding of natural language processing techniques and tools, machine learning Principles, and AI-generated content development
  • Conversational AI experience: Any of the following would be good: Kore.AI, Google Dialog Flow, Amelia, Yellow.AI
  • Familiarity with popular conversational AI platforms and frameworks (e.g., TensorFlow, PyTorch, or Hugging Face Transformers) is beneficial for leveraging pre-trained models and integrating prompt engineering strategies effectively.
  • Proven work experience as a Prompt Engineer or similar role
  • High-level familiarity with architecture and operation of large language models
  • Exceptional verbal and written communication skills for effective prompt design and collaboration with users, engineers, and product teams
  • Experience in creative writing or content creation is a plus.

Benefits

  • Equal Opportunity Employer.
  • Veteran Friendly Employer. SRS Distribution believes in hiring military veterans at any level for any position.