Prompt Engineer

Role & responsibilities:

Prompt Development and Optimization:

• Design, develop, and refine prompts to generate desired & relevant responses from AI models.
• Continuously test and iterate on prompts to improve quality and consistency.
• Experiment with different prompting techniques (e.g., few-shot, zero-shot, chain-of thought, self-validation, React) to achieve optimal results.

Model Selection and Usage:

• Select appropriate AI models based on project requirements, considering factors like model capabilities, cost, and latency.
• Effectively utilize the strengths and weaknesses of different models to achieve desired outcomes.

Prompt Vulnerability Assessment:

• Identify potential vulnerabilities in prompts, such as bias, hallucination, or adversarial attacks.
• Develop strategies to mitigate these vulnerabilities and ensure the safety and reliability of AI-generated content.

Evaluation and Improvement:

• Collaborate with teams to define evaluation metrics and methodologies.
• Analyze model performance and identify areas for improvement.
• Iterate on prompts and models to enhance overall performance.

Collaboration and Knowledge Sharing:

• Work closely with data scientists, machine learning engineers, and other stakeholders to understand project requirements and align prompt engineering strategies.
• Share knowledge and best practices within the team to foster a culture of continuous learning and improvement.

Preferred candidate profile:

• Experience with Python and the associated libraries.
• Good understanding of natural language processing (NLP) and machine learning foundation concepts.
• Proficiency in working with large language models (LLMs) like GPT-3.5, GPT-4o, or other advanced models.
• Experience with prompt engineering techniques and best practices.
• Ability to write clear, concise, and effective prompts.
• Strong analytical and problem-solving skills, with an eagerness to learn and adapt.
• Attention to detail and a commitment to quality.