Full-Time

Mid Conversational AI / Chatbot Developer

Techies4tech.ai · Toronto
Compensation
C$150000-C$219000 CAD/year
Experience
2-6 yrs

Job location

Street address
100 King Street West
City
Toronto
Region / state
ON
Postal code
M5X 1C0
Country
CA

Role Overview

Techies4tech.ai is hiring a Mid-level Conversational AI / Chatbot Developer to design and improve conversational experiences. This role focuses on building structured chatbot interactions through NLU/NLP design, dialogue flow development, and intent and entity modeling. The work contributes directly to the quality, clarity, and effectiveness of conversational systems.

Key Requirements

• NLU/NLP design — target L6 (Prof), must-have • dialogue flow — target L6 (Prof), must-have • intent & entity modeling, — target L6 (Prof), must-have • voice/text bot development, — target L6 (Prof), nice-to-have • analytics & continuous improvement — target L6 (Prof), nice-to-have • LLM/RAG integration — target L6 (Prof), nice-to-have • Working AI leverage — observed and scored, never assumed • 2–6 years of relevant experience

Responsibilities

Design conversational AI and chatbot experiences using NLU/NLP design principles. Create and refine dialogue flows that support clear, effective user interactions. Develop and maintain intent and entity models to improve how conversational systems interpret and respond to user input. Where applicable, contribute to voice or text bot development, support analytics and continuous improvement efforts, and assist with LLM/RAG integration.

About Techies4tech.ai

this position is for US based clients.

Why join

This role offers the opportunity to work directly on conversational AI and chatbot development with a focus on core interaction design and model structure. It is a clear fit for someone who wants to strengthen hands-on work in dialogue design, intent and entity modeling, and broader conversational system improvement. The scope also provides room to contribute to preferred areas such as analytics, voice or text bot development, and LLM/RAG integration where relevant.

Interested in this role?

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