AI Workflow Engineer - Freelance AI Trainer

Mindrift is a platform connecting specialists with AI projects from major tech innovators. The role is part of the Tendem project, focused on building intelligent automation systems powered by large language models (LLMs) within a hybrid AI and human environment.

• At least 3 years of relevant experience in AI automation, prompt engineering, workflow development, or software development.
• Bachelor's or Master’s Degree in Computer Science, Engineering, Data Science, Linguistics, or related fields is a plus.
• Strong experience working with LLM APIs (OpenAI, Claude, Gemini or similar) and integrating them into workflows.
• Proven ability to design prompt systems, chaining logic, and output optimization strategies.
• Solid background in API integrations, automation platforms, and multi-step AI pipelines.
• Experience structuring and preprocessing data for consistent AI performance (inputs/outputs, formatting, validation).
• Demonstrated experience building scalable AI-powered systems for real-world applications.
• Experience with personalization logic and dynamic content generation at scale.
• Strong understanding of LLM limitations (hallucinations, bias, context handling) and mitigation techniques.
• Experience integrating AI into outreach, analytics, or content automation pipelines.
• Strong attention to detail and commitment to output quality and consistency.
• Self-directed work ethic with the ability to troubleshoot and optimize AI systems independently.
• Portfolio or examples of AI workflows, prompt systems, or automation projects is a plus.
• English proficiency: Upper-intermediate (B2) or above (required).

• Design and evaluate workflows integrating LLM APIs (OpenAI, Claude, Gemini or similar).
• Build and optimize AI-powered automation systems for content generation, enrichment, and communication.
• Develop and refine prompt frameworks for consistent, high-quality outputs across workflows.
• Create systems for personalized automated outreach (email, messaging flows, lead enrichment).
• Structure and preprocess data to ensure stable model behavior and reliable outputs.
• Analyze and improve AI-driven pipelines for scalability, efficiency, and accuracy.