Conversational AI Engineer

The Conversational AI Engineer is the primary agent builder, responsible for developing and deploying intelligent conversational agents using Google Dialogflow CX. This role owns the conversation layer—from NLU model training and dialog flow implementation through webhook fulfillment and multi-channel deployment. Works shoulder-to-shoulder with the Architect on complex features and consumes RAG/LLM components built by the AI/ML Engineer. Performs preliminary technical testing on all personal deliverables before handoff to the BA for functional validation.

Key Responsibilities

- Design and implement conversational flows, intents, entities, and page/route structures in Dialogflow CX based on user stories and conversation design specifications. - Develop webhook fulfillment services in Python or to handle business logic, API calls, and dynamic responses. - Conduct NLU training, testing, and optimization to improve intent recognition accuracy and entity extraction. - Integrate generative AI components (built by the AI/ML Engineer) into agent flows—including LLM-powered responses, knowledge retrieval, and summarization features. - Deploy and configure agents across channels: web chat, telephony (CCAI), Google Chat, WhatsApp, and custom applications. - Design and implement webhook contracts and data schemas between Dialogflow CX agents and n8n workflows (built by the Automation Engineer). - Build and maintain n8n workflows for agent fulfillment when scope is straightforward, escalating complex automation to the Automation & Integration Engineer. - Implement error handling, fallback strategies, escalation logic, and graceful degradation in agent flows. - Perform preliminary technical testing (conversation path testing, webhook validation, intent accuracy checks, regression tests) on all personal deliverables before handoff to the BA. - Pair-program with the Architect on complex integrations and participate in code reviews. - Manage Dialogflow CX versioning, environment promotion, and agent deployment pipelines. - Participate in sprint planning and provide technical estimates for user stories.

Required Qualifications

- 4+ years of experience building conversational AI solutions, chatbots, or voice agents. - Strong proficiency with Google Dialogflow CX (flows, pages, routes, webhooks, test cases). - Advanced development skills in Python and/or with experience building and consuming REST APIs. - Understanding of NLU concepts: intent classification, entity extraction, context management, slot filling. - Familiarity with Google Cloud services: Cloud Functions, Cloud Run, Pub/Sub, Firestore, BigQuery. - Experience integrating with enterprise APIs and SaaS platforms (Salesforce, HubSpot, Jira, Slack). - Hands-on experience with n8n (preferred) or comparable automation platforms (Make, Zapier) for building workflows. - Proficiency with version control (Git), CI/CD, and agile development practices. - Disciplined approach to testing: comfortable writing unit tests, integration tests, and conversation test cases.

Nice to Have

- Experience with Vertex AI Agent Builder or Vertex AI Search and Conversation. - Familiarity with LangChain, LlamaIndex, or similar LLM orchestration frameworks. - Experience deploying agents in multilingual environments. - Knowledge of speech-to-text and text-to-speech services (Google Cloud Speech APIs). - Experience with telephony and contact center integrations.