Conversational AI Architect - Google Cloud Gemini CX

EPAM Systems; India; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

EPAM Systems is seeking a Principal Conversational AI Architect to design and scale enterprise-grade AI agents on Google Cloud. Lead hands-on engineering, guide production deployments and collaborate across data, security and product teams to deliver secure, high-volume conversational solutions.

Leverage Gemini CX, Dialogflow CX, Vertex AI and related services to build robust RAG pipelines, secure integrations, and actionable insights in complex cloud-native environments.

Qualifications

• 12-20 years of IT experience.
• Expertise in Gemini CX, Google Cloud CCAI, Vertex AI Agent Studio and the Advanced Agent Modeling (AAM) framework.
• Proven experience designing and deploying agentic and conversational AI systems.
• Expertise in Dialogflow CX including routing, tuning and telephony configurations.
• Experience building RAG solutions using Vertex AI Search with secure grounding.
• Proficiency in Python or Node.js with API/webhook/back-end development.
• Knowledge of GCP infrastructure, BigQuery, Looker Studio and cloud security controls.
• Proven experience moving agents from pilot to secure production environments.
• Nice to have Google Cloud Architect or Professional Data Engineer certs.
• Experience with dfcx-scrapi and enterprise customer service solutions.

Responsibilities

• Design and deploy enterprise-grade agentic and conversational AI solutions.
• Orchestrate hybrid conversational workflows with deterministic controls.
• Build and optimize RAG pipelines using Vertex AI Search.
• Develop secure backend integrations with Cloud Run/Functions and MCP.
• Implement security guardrails with Model Armor and IAM least-privilege.
• Build telemetry and analytics pipelines with BigQuery and CCAI Insights.
• Provide hands-on engineering leadership and production-grade code guidance.

Skills

Engineering leadership

Python/Node.js

APIs & webhooks

Security & compliance

Telemetry & analytics

Production-grade code

Tools

Gemini CX

Dialogflow CX

Vertex AI Agent Studio

Vertex AI

Cloud Run

Cloud Functions

Looker Studio

Terraform

IAM

VPC Service Controls

Model Armor

BigQuery

CCAI (Google Cloud Contact Center AI)

dfcx-scrapi

Job description

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