Senior Conversational AI Architect: Multi-Agent & Enterprise

EPAM Systems Inc; Argentina; Remote; ARS 3,200,000 - 5,200,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Job summary

EPAM Systems Inc. seeks a hands-on Conversational AI Architect to design, build, and deploy advanced agentic AI platforms.

You will bridge GenAI models with enterprise environments, orchestrate multi-agent workflows, and implement secure data pipelines across GCP services such as Gemini CX, Vertex AI, CCAI, and MCP. The role demands leadership in implementing state machines, RAG pipelines, and secure integrations, with a focus on reliability, compliance, and large-scale deployment.

Qualifications

• Minimum 5 years hands-on experience in AI/conversational platforms.
• Led engagements with teams of 5+ and managed client expectations.
• Deep experience across Google Cloud AI, Gemini CX, CCAI, and AAM frameworks.
• Strong conversation engineering skills, including Dialogflow CX and STT/TTS work.
• Proven Python/Node.js programming ability and cloud DevOps practices.

Responsibilities

• Construct and deploy autonomous, multi-agent systems using Gemini CX and Vertex AI Agent Studio.
• Oversee hybrid conversational flows with Dialogflow CX state machines and routing.
• Build and sustain Retrieval-Augmented Generation pipelines via Vertex AI Search.
• Engineer secure back-end integrations, connectors, and webhooks via Cloud Run/Functions.
• Ensure security with IAM, VPC-SC, Model Armor, and enterprise data controls.
• Create telemetry pipelines moving transcripts from Dialogflow into BigQuery and apply CCAI Insights.

Skills

Python

Node.js

Dialogflow CX

Google Cloud

Terraform

DevOps

Tools

Cloud Run

Cloud Functions

BigQuery

Looker Studio

Vertex AI

Gemini CX

dfcx-scrapi

Job description

EPAM Systems Inc. seeks a hands-on Conversational AI Architect to design, build, and deploy advanced agentic AI platforms.

You will bridge GenAI models with enterprise environments, orchestrate multi-agent workflows, and implement secure data pipelines across GCP services such as Gemini CX, Vertex AI, CCAI, and MCP. The role demands leadership in implementing state machines, RAG pipelines, and secure integrations, with a focus on reliability, compliance, and large-scale deployment.