Prompt Engineer

About the role

What you'll do

• Work closely with cross-functional teams and customers to understand project requirements and objectives for RAG 2.0 applications.
• Design, develop and document prompts and best practices for a wide range of use cases related to our customers.
• Conduct thorough analyses of LLM performance in response to different prompts, iterating on prompt design to improve model accuracy and coherence.
• Build a set of tutorials and interactive tools that teach the art of prompt engineering to our customers.

What we're seeking

• Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree preferred).
• Demonstrated expertise in NLP, particularly in the context of LLMs, with a deep understanding of model architectures, training methodologies, and evaluation metrics.
• Proficiency in programming languages commonly used in NLP, such as Python, along with experience working with deep learning frameworks like TensorFlow or PyTorch. Experience with DSPy and similar frameworks is a plus.
• Strong analytical and problem-solving skills, with a keen eye for detail and a passion for optimizing model performance through prompt engineering.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey complex concepts to non-technical stakeholders.
• Experience with version control systems (e.g., Git) and agile software development methodologies is a plus.
• Experience in the identification of vulnerabilities or security issues in LLMs or other AI models is a plus