Conversational AI Architect - Google Cloud Gemini CX

We are seeking a Conversational AI Architect to design, build and scale enterprise-grade conversational and agentic AI solutions on Google Cloud. This role combines deep technical expertise in Gemini CX, Dialogflow CX and Vertex AI with hands-on engineering leadership to move generative AI agents from pilot to secure, high-volume production environments.

Responsibilities

• Design and deploy enterprise-grade agentic AI and conversational AI solutions using Gemini CX, Vertex AI Agent Studio, Dialogflow CX and supporting Google Cloud AI services
• Orchestrate hybrid conversational workflows by combining generative playbooks and autonomous agent behaviors with deterministic Dialogflow CX state-machine controls
• Build and optimize RAG pipelines using Vertex AI Search to securely ground agents in enterprise documents, knowledge repositories and business data
• Develop secure backend integrations, connectors and webhooks using Cloud Run, Cloud Functions and Model Context Protocol (MCP) to integrate CRM, ERP and internal enterprise systems
• Implement security and compliance guardrails using Model Armor, VPC Service Controls, IAM least-privilege policies and appropriate data isolation controls
• Build conversation telemetry and analytics pipelines using BigQuery and CCAI Insights for error-taxonomy analysis, intent health, containment reporting and operational improvement
• Provide hands-on engineering leadership, write production-grade code, troubleshoot complex platform issues and guide solutions through production deployment and scale

Requirements

• 12-20 years of overall experience in IT
• Expertise in Gemini CX, Google Cloud Contact Center AI (CCAI), Vertex AI Agent Studio and the Advanced Agent Modeling (AAM) framework
• Proven experience designing and deploying agentic and conversational AI systems, including goal-oriented agents, multi-agent workflows and enterprise-scale customer interaction solutions
• Expertise in Dialogflow CX, including pages, parameters, conditional routing, transition routes, Speech-to-Text tuning, Text-to-Speech and telephony/SIP configurations
• Experience building Retrieval-Augmented Generation (RAG) solutions using Vertex AI Search and grounding AI agents securely with enterprise knowledge sources
• Proficiency in Python or Node.js, with hands-on development of APIs, webhooks, connectors and backend integrations using Cloud Run and Cloud Functions
• Knowledge of GCP infrastructure, BigQuery, Looker Studio, Terraform, IAM, VPC Service Controls, Model Armor, cloud security, data anonymization and enterprise security controls
• Proven experience moving generative AI agents from pilot/MVP stages into secure, scalable and high-volume production environments

Nice to have

• Google Cloud Professional Cloud Architect or Professional Data Engineer certification
• Completion of Google Cloud Agentic AI or Gemini Enterprise for Customer Experience (GECX) learning paths, and experience with automation libraries such as dfcx-scrapi
• Experience delivering high-volume customer service solutions in Financial Services, Telecom, Retail or Healthcare environments