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Description
Job Description: CCAI Architect (Intermediate) Total Experience Range: 8-15 years CCAI Experience: 4+ years Must-Have Skillsets: Dialogflow CX: Deep expertise in designing, building, and optimizing complex conversational agents. Conversational Design: Proven ability to create engaging and effective conversational experiences. NLU Tuning: Proficiency in fine-tuning NLU models for optimal intent recognition and entity extraction. Webhook Development: Strong hands-on experience with Node.js or Python for integrating external services and data sources. Generative AI: Understanding of generative AI techniques and their application within Dialogflow CX. Cloud Platforms: Familiarity with Google Cloud Platform (GCP), including deployment, CI/CD pipelines, and security best practices. Version Control: Proficiency in Git for collaborative development. Python Programming: Solid Python programming skills for data analysis, automation, and webhook development. GCP Certification: Relevant GCP certifications (e.g., Cloud Architect, Data Engineer) are preferred. Detailed Job Description: As a CCAI Architect, you will play a pivotal role in designing, developing, and deploying innovative conversational AI solutions. You will leverage your deep understanding of Dialogflow CX and conversational design principles to create robust and scalable agents that deliver exceptional user experiences. Key Responsibilities: Architecture Design: Develop comprehensive architectural blueprints for complex conversational AI systems, considering scalability, performance, and maintainability. NLU Optimization: Fine-tune NLU models to improve intent recognition and entity extraction accuracy, ensuring optimal agent performance. Webhook Development: Build and integrate custom webhooks using Node.js or Python to extend Dialogflow CX's capabilities and connect to external systems. Generative AI Integration: Explore and leverage generative AI techniques to enhance conversational experiences, such as generating natural language responses or personalized recommendations. Deployment and CI/CD: Collaborate with DevOps teams to deploy and maintain Dialogflow CX agents, ensuring smooth operations and efficient updates. Performance Optimization: Monitor agent performance metrics and identify opportunities for improvement, such as optimizing dialog flows, reducing response times, and enhancing error handling. Best Practices: Stay up-to-date with the latest advancements in conversational AI and industry best practices, sharing knowledge and mentoring team members. Collaboration: Work closely with cross-functional teams, including product managers, designers, and developers, to align on project goals and deliver high- quality solutions.
