Job Description
We are seeking a visionary Prompt Engineer to join our elite AI Research team in the heart of San Francisco. At Lumina Dynamics, we are building the cognitive layer of the internet, and we need a master of language to guide our Large Language Models (LLMs) to unprecedented heights.
Why This Role?
As a key driver of our AI strategy, you will be at the forefront of Generative AI innovation. We are proud to offer a $15,000 Sign-On Bonus to exceptional talent ready to define the future of human-computer interaction.
In this high-impact role, you will bridge the gap between theoretical AI research and practical, scalable applications. You will collaborate with data scientists, engineers, and product managers to deploy systems that are not just functional, but intelligent and empathetic.
Key Highlights:
- Work with cutting-edge models (GPT-4, Claude, Llama 3).
- Competitive compensation package with equity.
- Flexible remote/hybrid options within the SF Bay Area.
- Access to top-tier research infrastructure.
Responsibilities
- Design Prompt Architectures: Develop and implement sophisticated prompt templates and chain-of-thought strategies to optimize LLM performance for specific business use cases.
- Model Evaluation: Conduct rigorous A/B testing and human-in-the-loop evaluations to assess output quality, safety, and hallucination rates.
- Iterative Optimization: Continuously refine prompt engineering strategies based on performance metrics and user feedback loops.
- Knowledge Management: Create and maintain a repository of best practices, prompt libraries, and evaluation frameworks for the wider engineering team.
- Technical Documentation: Document prompt logic, edge cases, and system behaviors to ensure reproducibility and scalability.
- Collaboration: Partner with product teams to translate complex requirements into effective prompt engineering solutions.
Qualifications
- Experience: 3+ years of professional experience in Prompt Engineering, Computational Linguistics, or Natural Language Processing (NLP).
- Tech Stack: Proficiency in Python, LangChain, and familiarity with Hugging Face Transformers.
- Deep Learning: Strong understanding of transformer architectures, attention mechanisms, and fine-tuning methodologies.
- Communication: Exceptional written communication skills with the ability to write clear, concise, and persuasive text for both humans and machines.
- Problem Solving: Ability to deconstruct complex problems and design elegant, scalable prompt strategies to solve them.
- Education: Bachelor’s degree in Computer Science, Linguistics, Cognitive Science, or a related technical field (Master’s preferred).