Qentelli - Conversation Bot Engineer - NLP/Artificial Intelligence

Description :

About the Role :

As a Conversation Bot Engineer in our Global Markets environment, you will be a pivotal member of our team, responsible for the full lifecycle of cutting-edge chatbot and voicebot applications. You will drive the development, enhancement, modification, and maintenance of these critical tools, playing a key role in designing, coding, testing, debugging, and documenting programs. This position requires strong collaboration with business partners to define system requirements, as well as providing essential support for our corporate systems architecture. If you thrive on analyzing data, developing intelligent automation, and crafting market-leading conversational AI solutions, we encourage you to apply.

Key Responsibilities :

- Chatbot & Virtual Agent Development: Design, build, enhance, and maintain advanced chatbot and voicebot applications to meet evolving business needs within Global Markets.

- System Architecture Support: Provide robust support and contribute to the stability and performance of the corporate systems architecture related to conversational AI.

- Requirements Definition: Collaborate closely with business partners to gather, analyze, and define precise technical requirements for new and existing system applications.

- Data Analysis & Refinement: Conduct in-depth data analysis, develop automation scripts for efficient data handling, and leverage data refinement tools to optimize bot performance and intelligence.

- Solution Design & Strategy: Translate complex business requirements into optimal, innovative, and market-leading conversational AI solutions.

- Full-Stack Development: Design, code, test, debug, and document high-quality programs and features, ensuring reliability and scalability.

- Bot Training & Optimization: Train chatbots by meticulously analyzing historical chat conversations, large volumes of user-generated content, and processing diverse datasets.

Required Experience :

years of professional experience in virtual agent development and conversational AI.

Required Technical Skills :

- Virtual Agent & NLP Expertise: Proven, hands-on experience in the development of virtual agents (chatbots, voicebots) and a strong command of natural language processing (NLP) techniques.

- AI/NLP Platform Proficiency: Extensive experience working with one or more leading AI/NLP platforms, such as:

- DialogFlow

- Alexa

- Amazon Lex

- Rasa

- Luis

- Microsoft Bot Framework (including Azure Bot Service, LUIS, Azure Cognitive Services)

- IBM Watson

- Kore.AI, , Salesforce Einstein, (or similar)

- Programming Languages: Solid knowledge and practical experience with one or more of the following:

- Python

- JavaScript

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- Chatbot Training & Data Processing: Demonstrated experience in training conversational AI models through the analysis of historical chat conversations, large user-generated content, and effective data processing.

- NLP Fundamentals: Practical knowledge of formal syntax, formal semantics, corpus analysis, and robust dialogue management principles.

Required Soft Skills & Abilities :

- Strong Written Communication: Exceptional ability to articulate complex technical and business concepts clearly and concisely in written form.

- Continuous Learning Mindset: A proactive and enthusiastic approach to learning and rapidly adapting to the latest technologies and industry trends.

- Problem-Solving Acumen: Excellent analytical and critical thinking skills with a proven ability to solve complex technical and business challenges.

Generative AI (Gen AI) Skills (Highly Valued) :

- Conversational AI with Gen AI: Experience in building advanced conversational AI solutions utilizing:

- VertexAI Agent Builder

- Modern frameworks such as LangChain, CrewAI, Langraph.

- Agentic AI Architectures: Ability to design and implement sophisticated agentic AI architectures for autonomous task execution and intelligent workflows.

- Multi-Agentic AI Architectures: Expertise in developing and deploying multi-agentic AI architectures for collaborative and autonomous task resolution.

- Cloud Deployment & Optimization: Practical experience in deploying, managing, and optimizing AI models on leading cloud platforms, including:

- Google Vertex AI

- AWS

- Azure (specifically Azure AI Services, Azure OpenAI Service, Azure Bot Service, Azure Machine Learning)