Middle/Senior AI Trainer
Status: In Search
We are looking for an Middle/ Senior AI Trainer to enhance chatbot performance and implement AI-driven automation. While project details are still being defined, these roles will focus on optimizing virtual agents and ensuring smooth integrations within the Client’s ecosystem.
Project info: The Client is a leading provider of AI-powered virtual agents, helping businesses automate customer interactions with advanced conversational AI. Their no-code platform enables seamless chatbot development, API integrations, and continuous AI optimization.
Work format: Part-time (80 hours/month), with a potential increase to full-time
Location: Europe, Ukraine
Language: English (Upper-Intermediate/Advanced)
Experience & Expertise
2+ years of experience in AI Training, NLP, or Conversational AI
Hands-on experience with Boost.ai or other NLP/chatbot platforms (Amazon Lex, Dialogflow, LivePerson, Infobip, etc.)
Ability to train NLP models, fine-tune bots, create intents, entities, and dialogue flows
Expertise in Prompt Engineering to enhance AI assistant responses
Strong skills in testing and optimizing chatbots, troubleshooting issues, and improving UX
Experience working with large language models (GPT, Gemini, Claude)
Knowledge of knowledge base configuration for chatbots
Understanding of formal logic (working with conditions, if statements, and structured dialogue logic)
Ability to use API-returned variables for dynamic content creation
Nice to Have
Experience with APIs, SQL, Postman, and regular expressions (RegEx)
Additionally:
Direct client interaction and solution presentation
Ability to work with minimal supervision
Key Responsibilities
Provide AI Training services, supporting both standard and highly technical projects
Build and optimize conversational flows in Boost.ai
Write and refine training and test data to improve NLU model performance
Craft clear, engaging, and structured content for chatbot interactions (LLM support is available but should not be relied on)
Define logic structures to guide end users toward the most relevant information
Utilize variables returned from APIs to create personalized chatbot responses (no coding required)
Perform entity extraction and fine-tune chatbot recognition of user inputs
Process Flow:
HR pre-screen + English check (0.5 h)
Professional interview (1 h)