Conversational AI Engineer
Nexlify Solutions
About the role
About
As a Conversational AI Engineer, you’ll design and build intelligent chatbots and LLM-powered virtual assistants that transform how businesses interact with customers. You’ll apply natural language processing (NLP), large language models (LLMs), and machine learning to create conversational systems that automate support, drive engagement, and deliver personalized, human‑like experiences 24/7. You’ll collaborate with AI researchers, product managers, and developers to deploy solutions that blend cutting‑edge AI with real‑world impact.
Responsibilities
- Design, develop, and fine‑tune chatbots and conversational AI systems.
- Implement NLP pipelines for intent recognition, entity extraction, and dialogue management.
- Integrate large language models (e.g., GPT, LLaMA, or fine‑tuned transformers) into applications.
- Collaborate with back‑end engineers to connect conversational systems with APIs and databases.
- Optimize AI models for accuracy, speed, and scalability.
- Stay current with the latest advancements in LLMs, Retrieval‑Augmented Generation (RAG), and conversational UX.
- Provide expert guidance on developing an AI strategy.
Preferred Qualifications
- Bachelor’s/Master’s in Computer Science, AI, Computational Linguistics, or related field.
- Strong programming skills in Python (NLP libraries like SpaCy, Hugging Face, NLTK).
- Experience with transformer‑based models (BERT, GPT, etc.).
- Familiarity with conversational AI frameworks (e.g., Rasa, LangChain, Botpress).
- Knowledge of APIs and back‑end integration.
- Strong problem‑solving and communication skills.
- Bonus: Experience with multilingual NLP or voice‑based assistants.
Career Details
Full-time • Canada • C$95k – 120k / year
Role
Conversational AI Engineer (LLMs, NLP)
As a Conversational AI Engineer, you’ll design and build intelligent chatbots and LLM‑powered virtual assistants that deliver cross‑platform AI‑powered user experiences on iOS and Android, and build scalable web apps by combining modern front‑end frameworks with powerful back‑end systems.
Reference
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Requirements
- Strong programming skills in Python (NLP libraries like SpaCy, Hugging Face, NLTK).
- Experience with transformer-based models (BERT, GPT, etc.).
- Familiarity with conversational AI frameworks (e.g., Rasa, LangChain, Botpress).
- Knowledge of APIs and back-end integration.
- Strong problem-solving and communication skills.
Responsibilities
- Design, develop, and fine-tune chatbots and conversational AI systems.
- Implement NLP pipelines for intent recognition, entity extraction, and dialogue management.
- Integrate large language models (e.g., GPT, LLaMA, or fine-tuned transformers) into applications.
- Collaborate with back-end engineers to connect conversational systems with APIs and databases.
- Optimize AI models for accuracy, speed, and scalability.
- Stay current with the latest advancements in LLMs, Retrieval-Augmented Generation (RAG), and conversational UX.
Skills
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