Position Overview:

As a Prompt Engineer / AI Coding Trainer, you will work on designing, testing, and refining input prompts for AI language models to generate the most accurate and useful responses. The role also involves evaluating and improving the outputs to align with specific use cases or organizational goals.

This role combines technical acumen, critical thinking, and a passion for AI to continuously improve AI-driven results.

Key Responsibilities:

• Develop, test, and optimize input prompts for AI models to achieve desired outcomes.

• Analyze and review AI-generated responses for quality, accuracy, and relevance.

• Edit, refine, and improve both the prompts and the model’s responses to meet business or project needs.

• Collaborate with developers, data scientists, and other stakeholders to integrate the AI’s outputs into workflows or applications.

• Document prompt strategies, improvements, and best practices for future use.

• Stay updated on advancements in AI and natural language processing (NLP) to refine techniques.

• Use feedback and analytics to iteratively enhance AI interaction outcomes.

Qualifications & Requirements:

Technical Skills & Experience:

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field.

• Proficiency in programming languages like Python, JavaScript, Java, or C++.

• Familiarity with frameworks, libraries, and APIs used in modern software development.

• Experience in reviewing code for quality, efficiency, and adherence to standards.

• Knowledge of debugging tools and techniques for identifying and resolving coding issues.

• Strong understanding of AI and machine learning concepts, particularly large language models (LLMs).

• Familiarity with how LLMs function, particularly for coding, debugging, and system design tasks.

• Knowledge of prompt engineering strategies for developer-specific use cases.

• Experience using tools like OpenAI GPT, Anthropic Claude, or similar models.

Soft Skills:

• Strong written and verbal communication skills in English.

• Ability to craft clear, precise, and effective prompts and instructions for AI systems.

• Ability to identify and correct ambiguities, inconsistencies, or errors in AI outputs.

• Critical thinking and problem-solving abilities to evaluate and improve AI outputs.

• Strong attention to detail for assessing the relevance and quality of AI responses.

• Ability to work independently and collaboratively in dynamic teams.