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AI Solutions Architect
2 months ago
We are recruiting for a passionate Solutions Architect to join an expanding team to support the evolution of our cutting-edge conversational AI solutions, using LLM and associated techniques to drive faster delivery and more robust solutions to our clients.
You will work in the AI & Data Practice as a member of the solutions team and ensure the optimal performance & delivery of our conversational AI applications (Amelia, Kore, Omilia) and the use of generative AI to improve customer & developer lo code experience.
This is a client facing role.
The Solutions Architect at Bell will work in a dynamic and collaborative environment with opportunities for professional growth and skill development. The role will may involve collaboration with cross-functional teams, engagement with external partners or clients, and participation in AI-related industry events or conferences. Bell Integration is committed to fostering a diverse and inclusive workplace and encourages individuals from all backgrounds to apply.
Responsibilities:
Conversational AI Solutioning:
- Analyse client or organizational needs to determine how conversational AI can enhance customer interactions.
- Responsible for the High Level Designs of any solution and handing over to other members of the team for further development
- Develop and oversee the implementation of conversational AI platforms, including chatbots and voice assistants and integration of LLMs into the process
- Work with multiple projects or teams on complex problems that require broad architectural thinking.
- Collaborate with cross-functional teams, including data scientists, engineers, and UX designers, to create seamless user experiences.
- Monitor and optimize the performance of conversational AI systems, ensuring high accuracy and user satisfaction.
- Stay updated with the latest advancements in AI, machine learning, and natural language processing technologies.
- Provide technical leadership and mentorship within the AI development team.
Generate Actionable Insights:
- Collaborate with cross-functional teams to identify opportunities for improving the conversational AI user experience and driving business impact.
- Develop and present reports, dashboards, and visualizations to communicate insights to stakeholders.
- Continuous Improvement
- Stay informed about the latest advancements in conversational AI technologies and industry best practices.
- Contribute to the continuous improvement of the conversational AI applications by providing feedback and recommendations for future developments. Participate in the development of AI training data sets and annotation guidelines to improve the accuracy and relevance of the AI models.
Stakeholder Collaboration:
- Collaborate with the customer success team and assist in addressing customer feedback, inquiries, and issues related to conversational AI interactions.
- Engage with internal stakeholders to gather requirements, understand business objectives, and align AI strategies with organizational goals.
Experience/skills:
- Bachelor’s degree in Computer Science, Data Science, Information Technology, or related subject is required or proven experience in a similar role
- Familiarity with conversational AI platforms, chatbot frameworks, voice recognition technologies, and customer interaction analytics tools
- Excellent communication and presentation skills to articulate complex data findings and insights to both technical and non-technical stakeholders.
- Strong analytical, problem-solving, and critical thinking skills with a keen attention to detail.
- Experience with AI and NLP technologies, particularly in the context of conversational interfaces.
- Knowledge of Large Language Models, retrieval-augmented generation and generative AI concepts
- Experience in data analysis, AI analytics, or related roles, preferably within the context of conversational AI or natural language processing.
- Knowledge of machine learning concepts, NLP techniques, and AI model valuation metrics is desirable.
- .Ability to work collaboratively in a cross-functional environment and adapt to evolving requirements and priorities.
Additional Requirements:
- Comfortable the proficiency in data analysis tools and languages such as Python, R, SQL, or related platforms for analysing and visualizing large datasets is a plus
- Knowledge of Generative AI in the Conversational AI area is a plus.
- Knowledge of software development methodologies and agile principles is beneficial.
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