2 Conversational Design Jobs

At SquadStack, were building GenAI AI Agents that are intuitive, intelligent, and capable of truly human-like conversations. As a Voice AI Product Analyst, youll help bring AI agents to life by transforming real-world business needs into smart, scalable voice experiences. This is a hands-on role for someone with an entrepreneurial mindset who wants to learn fast, build boldly, and shape how people interact with AI. Where you'll make an Impact Convert business goals into agentic workflows by designing and iterating on conversation flows and logic Write and test prompts that bring out the best from LLMs in a voice-first context. Evaluate, debug, and improve voicebot performance using structured test cases and success metrics. Work closely with engineering, data, sales, and marketing to align voice AI Agent behavior with real customer use cases. Build tools, prompt templates, and reusable components to scale development efficiently. Document strategies and continuously improve based on data insights and user feedback. Skills that make you a great fit Solid understanding of LLMs and prompt engineering — including few-shot, zero-shot, role prompting, and persona shaping. Comfort with Python and SQL to prototype, automate tests, and analyze conversational data. Strong written and verbal communication in English and Hindi (you’ll write for real people, not robots). A strong sense of ownership and entrepreneurial mindset — you move fast, ask the right questions, and find your own path when needed. A self-starter mindset — you're a “ manager of one ” who can take ownership and drive outcomes. Ability to analyze business requirements and translate them into smart, human-like conversational agents. Qualification Recent graduate in Computer Science, Data Science, Linguistics, AI, Product Design, or a related field. Exposure to large language models (LLMs) like ChatGPT, Claude, Gemini, or similar - academic, personal, or internship projects are welcome. Basic proficiency in Python - able to call APIs, write scripts, or analyze data. Working knowledge of SQL - able to run queries to explore or report on data. Passion for AI, voice tech, or conversational UX - you’ve played with bots, experimented with prompts, or imagined how a smart assistant should talk. 0-1 years of experience working in similar roles & projects Logistics Compensation: Competetive! Joining: ASAP! Location: Noida

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.