
Artificial Intelligence Prompt Specialist
4 days ago
We are seeking a highly skilled AI Prompt Engineer to design, refine, and optimize prompts that drive advanced AI systems to deliver accurate, reliable, and contextually aligned outputs.
This role blends creativity, technical expertise, and critical thinking to push the boundaries of what AI models can achieve in real-world applications. You will collaborate closely with product, engineering, design, and operations teams to ensure our AI-powered tools and solutions meet user needs, align with business objectives, and deliver exceptional performance.
Design, develop, and evaluate effective prompts to optimize AI model outputs across various use cases (e.g., chat, search, analysis, content generation).
Conduct systematic testing and iteration to evaluate prompt performance and improve accuracy, reliability, and safety.
Translate complex user requirements and business goals into AI-driven workflows.
Build and maintain a knowledge base of prompt strategies, best practices, and reusable templates.
Collaborate with engineers to fine-tune model parameters, integrate prompts into production systems, and evaluate results at scale.
Work with cross-functional teams (product managers, designers, domain experts) to align AI interactions with user expectations.
Monitor AI performance and proactively identify areas for refinement.
Stay up-to-date with the latest advancements in AI, LLMs, and prompt engineering techniques.
Our ideal candidate has:
Proven experience working with Large Language Models (LLMs) such as GPT or similar.
Strong analytical and problem-solving skills with a systematic approach to experimentation.
Ability to craft precise, creative, and context-aware prompts that improve AI outputs.
Familiarity with programming/scripting languages (Python or JavaScript) for testing and automation.
Experience in data analysis, A/B testing, or evaluation metrics for AI performance.
Curiosity and adaptability to work in a fast-moving, innovation-driven environment.
Experience or knowledge of n8n or Make.
While not required, having a background in computational linguistics, human-computer interaction, or cognitive science is beneficial.
Knowledge of fine-tuning or training AI/ML models is also desirable.
Additionally, experience building AI-powered applications or tools and familiarity with ethical AI, bias mitigation, and safety considerations in LLMs are valuable assets.
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