AI Architect

EPAM Systems; Brasil; Remote; BRL 350,000 - 520,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling & certification

Job summary

EPAM Systems is seeking a deeply technical Forward Deployed Engineer to architect and launch agentic AI solutions in complex enterprise environments. You will write production-ready code, orchestrate multi-agent workflows, and integrate with Gemini CX and Vertex AI.

Responsibilities include designing end-to-end conversations, tuning along state machines in Dialogflow CX, and building secure data pipelines using Vertex AI, Cloud Run, and Cloud Functions.

Qualifications

• 5+ years of applicable professional background.
• Experience leading teams of 5+ full-time staff.
• Hands-on with Google Cloud AI, Gemini CX, and AAM framework.

Responsibilities

• Architect and launch multi-agent systems using Gemini CX and Vertex AI Agent Studio.
• Coordinate blended conversational flows with state-machine monitoring in Dialogflow CX.
• Build Retrieval-Augmented Generation pipelines with Vertex AI Search for enterprise knowledge sources.
• Create secure backend connectors via Cloud Run/Functions to bridge conversations with CRMs/ERPs.

Skills

Python

Node.js

Dialogflow CX

GCP

Conversation engineering

DevOps

Tools

Terraform

Cloud Run

Cloud Functions

BigQuery

Job description

We're in search of a deeply technical, implementation-focused Forward Deployed Engineer (FDE) / Conversational AI Architect to architect, construct, and launch cutting-edge agentic AI solutions. In this capacity, you'll serve as the critical link connecting frontier Generative AI models with intricate enterprise-grade production environments. This role goes well beyond architecture diagrams; you'll be writing production-ready code, coordinating multi-agent workflows through Gemini CX / Vertex AI Agent Builder, managing deterministic state machines within Dialogflow CX, and constructing secure cloud data pipelines built on the Advanced Agent Modeling (AAM) frameworkResponsibilitiesArchitect and launch purpose-driven, self-operating multi-agent systems through Gemini CX and Vertex AI Agent Studio, pushing customer interactions beyond simple deflection toward complete end-to-end resolutionCoordinate blended conversational flows by pairing generative playbooks with exact state-machine monitoring inside Dialogflow CX, making use of Pages, Parameters, Conditional Routing, and Transition RoutesConstruct, refine, and sustain Retrieval-Augmented Generation (RAG) pipelines through Vertex AI Search to anchor agents securely against unstructured enterprise knowledge sourcesBuild and launch secure backend connectors, integrations, and webhooks via Cloud Run, Cloud Functions, and the Model Context Protocol (MCP) to bridge conversational layers with enterprise CRMs, ERPs, and internal data systemsApply enterprise-level data security and regulatory compliance by setting up Model Armor constraints, establishing VPC Service Controls (VPC-SC), and upholding rigorous IAM least-privilege standardsConstruct telemetry pipelines that route raw conversation transcripts from Dialogflow into BigQuery, applying CCAI Insights to power extensive error-taxonomy assessments, intent health evaluation, and containment rate trackingRequirementsAt least 5 years of applicable professional backgroundA minimum of 2 years spent in Senior, Lead, Manager, or Owner-level capacitiesEstablished history overseeing engagements involving teams of 5 or more full-time staffExtensive, hands-on background across the Google Cloud AI landscape, encompassing Gemini CX, Google Cloud Contact Center AI (CCAI), and the Advanced Agent Modeling (AAM) frameworkClear expertise in conversation engineering, spanning Dialogflow CX, Speech-to-Text (STT) tuning (phrase hints, audio profiles), Text-to-Speech (TTS), and telephony/SIP trunking setupsSolid programming capability in Python or Node.js, with background crafting custom automation scripts or applying Google Cloud wrapper libraries like dfcx-scrapi regarded as a notable plusStrong background with GCP infrastructure and DevOps tools, including Cloud Run, Cloud Functions, BigQuery, Looker Studio, and Infrastructure-as-Code methods using TerraformHands-on understanding of cloud security fundamentals, data anonymization approaches, and separating model training boundaries within enterprise tenant limitsEstablished record of advancing generative AI agents from pilot/MVP phases into fully scaled, live production systems supporting millions of end usersFluent English communication abilities at a B2 level or aboveNice to haveCertification as a Google Cloud Professional Cloud Architect or Professional Data EngineerCompleted Google Cloud's official Agentic AI on Google Cloud or Gemini Enterprise for Customer Experience (GECX) learning tracksBackground launching high-volume customer service platforms within Financial Services, Telecom, Retail, or Healthcare industriesWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.