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) framework Responsibilities Architect 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 resolution Coordinate blended conversational flows by pairing generative playbooks with exact state-machine monitoring inside Dialogflow CX, making use of Pages, Parameters, Conditional Routing, and Transition Routes Construct, refine, and sustain Retrieval-Augmented Generation (RAG) pipelines through Vertex AI Search to anchor agents securely against unstructured enterprise knowledge sources Build 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 systems Apply 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 standards Construct 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 tracking Requirements At least 5 years of applicable professional background A minimum of 2 years spent in Senior, Lead, Manager, or Owner-level capacities Established history overseeing engagements involving teams of 5 or more full-time staff Extensive, hands-on background across the Google Cloud AI landscape, encompassing Gemini CX, Google Cloud Contact Center AI (CCAI), and the Advanced Agent Modeling (AAM) framework Clear expertise in conversation engineering, spanning Dialogflow CX, Speech-to-Text (STT) tuning (phrase hints, audio profiles), Text-to-Speech (TTS), and telephony/SIP trunking setups Solid 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 plus Strong background with GCP infrastructure and DevOps tools, including Cloud Run, Cloud Functions, BigQuery, Looker Studio, and Infrastructure-as-Code methods using Terraform Hands-on understanding of cloud security fundamentals, data anonymization approaches, and separating model training boundaries within enterprise tenant limits Established record of advancing generative AI agents from pilot/MVP phases into fully scaled, live production systems supporting millions of end users Fluent English communication abilities at a B2 level or above Nice to have Certification as a Google Cloud Professional Cloud Architect or Professional Data Engineer Completed Google Cloud's official Agentic AI on Google Cloud or Gemini Enterprise for Customer Experience (GECX) learning tracks Background launching high-volume customer service platforms within Financial Services, Telecom, Retail, or Healthcare industries
