Job Description
Are you ready to shape the future of Artificial Intelligence? Nexus AI Innovations is looking for a top-tier Senior Prompt Engineer to join our dynamic team in Plano, TX. We are on the cutting edge of developing enterprise-grade LLM solutions, and we need your expertise to bridge the gap between human intent and machine output.
In this high-impact role, you will be responsible for crafting the logic that drives our AI agents. If you have a passion for language, logic, and technology, this is your chance to work with industry leaders on projects that redefine user interaction.
Responsibilities
- Architect and implement advanced prompt strategies for Large Language Models (LLMs) including GPT-4, Claude, and PaLM.
- Optimize prompt chains and workflows to ensure high accuracy, coherence, and safety in AI responses.
- Perform rigorous A/B testing and iterative evaluation to refine model outputs based on user feedback.
- Collaborate with Data Scientists and Product Managers to translate business requirements into technical prompt specifications.
- Develop and maintain a central repository of prompt templates and best practices for the engineering team.
- Debug complex AI behaviors and troubleshoot edge cases in real-time production environments.
- Stay ahead of the curve by researching new prompting techniques and NLP advancements.
Qualifications
- Minimum of 3-5 years of experience in technical writing, content strategy, or software engineering.
- Deep understanding of prompt engineering concepts such as Chain-of-Thought, few-shot prompting, and system instruction tuning.
- Proficiency in Python or JavaScript for scripting and automating prompt workflows.
- Strong analytical skills with the ability to deconstruct complex problems and design logical solutions.
- Excellent verbal and written communication skills to articulate technical concepts clearly.
- Bachelor’s degree in Computer Science, Linguistics, English, or a related technical field.
- Experience working in Agile/Scrum environments is highly preferred.