Location: LATAM
English Level: B2 B2
About the Project: technology Company
We are seeking a highly technical, hands-on Forward Deployed Engineer (FDE) / Conversational AI Architect to design, build, and deploy next-generation agentic AI systems. In this role, you will act as the engineering
bridge between frontier Generative AI models and complex enterprise production infrastructure.
You will not just design architectures; you will write production-grade code, orchestrate multi-agent workflows using Gemini CX / Vertex AI Agent Builder, maintain deterministic state machines via Dialogflow
CX, and build secure cloud data pipelines using the Advanced Agent Modeling (AAM) framework.
Key Responsibilities
- Agentic AI Architecture: Design and deploy goal-oriented, autonomous multi-agent systems utilizing Gemini CX / Vertex AI Agent Studio, moving customer touchpoints from basic deflection to true end-to-end resolution.
- Deterministic & Generative Flow Engineering: Orchestrate hybrid conversational workflows by combining generative playbooks with precise state-machine tracking in Dialogflow CX (Pages, Parameters, Conditional Routing, and Transition Routes).
- Enterprise Grounding (RAG): Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Search to ground agents securely in unstructured enterprise knowledge bases.
- Backend Integrations & Webhooks: Develop and deploy secure backend integrations, connectors, and webhooks using Cloud Run, Cloud Functions, and the Model Context Protocol (MCP) to link conversational layers to enterprise CRMs, ERPs, and internal databases.
- DevOps & Security Guardrails: Enforce enterprise-grade data security and compliance by implementing Model Armor constraints, configuring VPC Service Controls (VPC-SC), and enforcing strict IAM least-privilege boundaries.
- Data Piping & Telemetry: Build telemetry pipelines that stream raw conversation transcripts out of Dialogflow into BigQuery, utilizing CCAI Insights to conduct massive error-taxonomy reviews, intent health analysis, and containment rate reporting.
Must Have Skills:
Required Technical Skills & Qualifications
- Google Cloud AI Ecosystem: Deep hands-on experience with Gemini CX, Google Cloud Contact Center AI (CCAI), and the Advanced Agent Modeling (AAM) framework.
- Conversation Engineering: Proven track record in Dialogflow CX, Speech-to-Text (STT) tuning (phrase hints, audio profiles), Text-to-Speech (TTS), and telephony/SIP trunking configurations.
- Programming & Automation: Strong proficiency in Python or Node.js. Experience writing custom automation scripts or utilizing Google Cloud wrapper libraries (e.g., dfcx-scrapi) is a massive plus.
- GCP Infrastructure & DevOps: Solid experience with Cloud Run, Cloud Functions, BigQuery, Looker Studio, and Infrastructure-as-Code (Terraform).
- Security First Mindset: Practical knowledge of cloud security, data anonymization, and isolating model training perimeters within enterprise tenant constraints.
- Production Experience: A history of successfully moving generative AI agents out of the "Pilot/MVP" stage into fully scaled, live production environments facing millions of users.
Engagement Duration:
1 year
