EU remote
AI Response Labeler / Annotator
About this role
About Blueprint Blueprint is a technology solutions firm headquartered in Bellevue, Washington, with teams across the United States. We help organizations turn complex challenges into meaningful outcomes by connecting strategy and execution across AI, cloud, data, product development, and emerging technology. Our culture is built by people who care deeply about doing exceptional work. We set high standards, take ownership, and continually challenge ourselves and one another to be better.
We work hard, support each other, and take genuine pride in what we deliver for our clients, partners, and teams. At Blueprint , you’ll work alongside talented people with different experiences, expertise, and perspectives. You’ll have opportunities to take on meaningful challenges, expand your skills, and see the impact of what you build. Bring your perspective. Raise the standard. Build what matters. About the Role We’re looking for an English-language AI Response Labeler / Annotator to evaluate the quality of AI-generated responses.
This role calls for strong English comprehension, analytical judgment, and the ability to apply detailed guidelines consistently across a high volume of work. You’ll compare responses generated by different AI models and determine which one better meets a user’s needs. You’ll consider factual accuracy, reasoning, relevance, completeness, instruction following, safety, clarity, tone, and overall usefulness. The prompts, responses, annotation guidelines, training, and written evaluation work for this role are in English.
What You'll Do Perform side-by-side comparisons of AI-generated responses and select the stronger response using established evaluation criteria. Assess responses for factual accuracy, relevance, completeness, reasoning, instruction following, clarity, safety, tone, and usefulness. Evaluate varied tasks, including questions and answers, web-search results, file-based and image-based responses, content generation, and single-turn or multi-turn conversations.
Identify meaningful differences between responses, such as unsupported claims, missed instructions, weak reasoning, and incomplete answers. Apply detailed, scenario-specific guidelines and make sound decisions when an example does not provide an obvious answer. Write concise, evidence-based explanations for your decisions when required. Meet established productivity expectations while maintaining accuracy and consistent judgment.