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 India Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Unlimited access to LinkedIn learning solutions Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: Health benefits Retirement benefits Paid time off Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)