builder
An AI Agent Builder creates AI systems that plan steps, call tools, use business context, and complete bounded workflows with human fallback.
Core skills
Tool callingWorkflow orchestrationRAG
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AI Careers
A structured glossary for AI-native roles, built for SEO, education, employer conversion, and talent conversion.
An AI Agent Builder creates AI systems that plan steps, call tools, use business context, and complete bounded workflows with human fallback.
Core skills
An AI Automation Specialist builds maintainable automations that connect AI tools, business apps, data updates, alerts, and human review.
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An AI Engineer designs, builds, evaluates, and ships AI-powered software systems that work inside real product or business workflows.
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An AI Product Engineer turns AI product ideas into usable features by combining product thinking, application engineering, model integration, and iteration.
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An LLM Engineer specializes in building reliable language-model features through prompting, retrieval, evaluation, and production integration.
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An AI Application Engineer applies Application development, API integration, and Production debugging to turn AI use cases into clear, reviewable work outcomes.
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An AI Builder applies AI prototyping, Workflow design, and Tool integration to turn AI use cases into clear, reviewable work outcomes.
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An AI Consultant applies Use-case discovery, Implementation planning, and Stakeholder alignment to turn AI use cases into clear, reviewable work outcomes.
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An AI Data Engineer applies Data pipelines, Vector data preparation, and Data quality checks to turn AI use cases into clear, reviewable work outcomes.
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An AI Full-stack Engineer applies Frontend development, Backend APIs, and AI feature integration to turn AI use cases into clear, reviewable work outcomes.
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An AI Product Manager applies AI product strategy, Use-case prioritization, and Experiment planning to turn AI use cases into clear, reviewable work outcomes.
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An AI Solutions Architect applies Solution design, Technical scoping, and System integration to turn AI use cases into clear, reviewable work outcomes.
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An AI Workflow Designer applies Process modeling, Automation mapping, and Human-in-the-loop design to turn AI use cases into clear, reviewable work outcomes.
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A Machine Learning Engineer applies Model training, Feature pipelines, and ML deployment to turn AI use cases into clear, reviewable work outcomes.
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A Prompt Engineer applies Prompt design, Instruction testing, and Output evaluation to turn AI use cases into clear, reviewable work outcomes.
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An AI Integration Specialist applies API integration, Systems mapping, and Deployment coordination to turn AI use cases into clear, reviewable work outcomes.
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An AI Operations Specialist applies Operational workflows, AI tool administration, and Process monitoring to turn AI use cases into clear, reviewable work outcomes.
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An AI Research Engineer applies Experiment design, Model evaluation, and Research implementation to turn AI use cases into clear, reviewable work outcomes.
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An AI Trainer applies Enablement design, AI usage coaching, and Evaluation rubrics to turn AI use cases into clear, reviewable work outcomes.
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An AI UX Designer applies AI interaction design, Conversation design, and Prototype testing to turn AI use cases into clear, reviewable work outcomes.
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