Conversational AI Engineer

at  Quantiphi

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Work Location: Remote (Canada/USA)
As a Conversational AI Engineer at Quantiphi, you will leverage advanced machine learning (ML) and artificial intelligence (AI) technologies in the cloud to enhance operational efficiency, manage risk, elevate customer engagement, and derive actionable insights from data.

Responsibilities:

• Demonstrated experience in managing and delivering successful conversational AI initiatives in large enterprise environments.
• Work closely with cross-functional teams to seamlessly integrate conversational AI solutions with existing systems and workflows.
• Apply user-centered design principles to create conversational AI systems that prioritize the needs of end-users.
• Expertise in analyzing and enhancing conversational AI performance through metrics and feedback, driving continuous improvement.
• Extensive experience designing and deploying conversational AI solutions for both voice and chat platforms, utilizing tools like AWS Lex and Bedrock.
• Conduct audits of existing conversational flows and bots, identifying optimization opportunities.
• Evaluate AI-driven solutions across business units, ensuring alignment with specific use case requirements.
• Craft comprehensive conversational designs, including intents, utterances, and slot types, ensuring intuitive and user-friendly experiences that meet both business objectives and user needs.
• Solid foundation in computational linguistics and semantic analysis techniques to enhance the accuracy and understanding of conversational AI models.
• Experience with Retrieval-Augmented Generation (RAG) techniques to optimize conversational AI performance.

Required Skills:

• Strong understanding of NLP concepts, with practical experience in developing and optimizing NLP models for conversational interfaces.
• Proficiency in data analysis and machine learning, leveraging these skills to improve AI outcomes.
• Experience in prototyping and testing conversational AI solutions to ensure high-quality performance and user satisfaction.
• Stay updated on the latest advancements in conversational AI, integrating new technologies as appropriate.
• Excellent verbal and written communication skills, capable of conveying technical concepts to both technical and non-technical stakeholders.
• Strong collaborator with cross-functional teams and demonstrated leadership in mentoring and guiding junior engineers.
• High attention to detail, particularly in developing scenarios for test cases.

Certifications & Education:

• Bachelor’s degree in Computer Science, Artificial Intelligence, Human-Computer Interaction, Computational Linguistics, or a related field (Master’s preferred).
• AWS Certifications:
• AWS Certified Solutions Architect – Associate or Professional
• AWS Certified Machine Learning - Specialty

What is in it for you:

• Be part of the fastest-growing AI-first digital transformation and engineering company in the world
• Be a leader of an energetic team of highly dynamic and talented individuals
• Exposure to working with fortune 500 companies and innovative market disruptors
• Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud

If you like wild growth and working with happy, enthusiastic over-achievers, you’ll enjoy your career with us!

• Demonstrated experience in managing and delivering successful conversational AI initiatives in large enterprise environments.
• Work closely with cross-functional teams to seamlessly integrate conversational AI solutions with existing systems and workflows.
• Apply user-centered design principles to create conversational AI systems that prioritize the needs of end-users.
• Expertise in analyzing and enhancing conversational AI performance through metrics and feedback, driving continuous improvement.
• Extensive experience designing and deploying conversational AI solutions for both voice and chat platforms, utilizing tools like AWS Lex and Bedrock.
• Conduct audits of existing conversational flows and bots, identifying optimization opportunities.
• Evaluate AI-driven solutions across business units, ensuring alignment with specific use case requirements.
• Craft comprehensive conversational designs, including intents, utterances, and slot types, ensuring intuitive and user-friendly experiences that meet both business objectives and user needs.
• Solid foundation in computational linguistics and semantic analysis techniques to enhance the accuracy and understanding of conversational AI models.
• Experience with Retrieval-Augmented Generation (RAG) techniques to optimize conversational AI performance