Job Description
Are you a wordsmith with a passion for artificial intelligence? Apex Logic Systems is seeking a visionary Senior Prompt Engineer to join our dynamic team in Cincinnati, OH. As a leader in generative AI solutions, we are looking for a talent who can bridge the gap between human intent and machine logic to build the next generation of conversational AI agents.
In this role, you will define the 'personality' and capabilities of our large language models (LLMs). You will craft, test, and refine prompts that drive high-quality, context-aware outputs for enterprise clients. If you thrive in a fast-paced, innovative environment and want to shape the future of AI interaction, we want to hear from you.
Responsibilities
- Design & Development: Create complex, multi-turn prompt chains and system instructions for LLMs (GPT-4, Claude, Llama) to maximize accuracy and reduce hallucinations.
- Model Fine-Tuning: Collaborate with data science teams to curate datasets and fine-tune models based on business-specific requirements.
- RAG Implementation: Optimize Retrieval-Augmented Generation pipelines to ensure our AI agents have access to the most relevant, up-to-date enterprise knowledge.
- Performance Analysis: Continuously monitor model outputs, conduct A/B testing on different prompt strategies, and iterate based on user feedback and performance metrics.
- Documentation: Maintain detailed documentation of prompt libraries, optimization strategies, and best practices for the engineering team.
Qualifications
- Experience: 3+ years of experience in Prompt Engineering, NLP, or a related AI field.
- Technical Skills: Proficiency in Python, SQL, and familiarity with API integrations (OpenAI API, Anthropic API).
- LLM Knowledge: Deep understanding of Large Language Model architectures, context windows, and tokenization.
- Education: Bachelor’s degree in Computer Science, Linguistics, Cognitive Science, or a related field.
- Problem Solving: Strong analytical thinking skills with the ability to debug complex conversational flows.