About this Conversational AI Engineer - Google/GECX & Code Agents role at Ttecdigital
As a Conversational AI Engineer specializing in Gemini Enterprise for Customer Experience (GECX), you will design, deploy, and optimize next-generation, customer-facing agentic workflows. You will work on a unified platform that bridges the gap between digital discovery (via Google Search and Maps) and front-line customer operations (chat, voice, and retail/commerce touchpoints).
You will use Customer Experience Agent Studio (CX Agent Studio) to build multi-agent applications, but your core focus will be implementing Code Agents—leveraging programmatic SDKs (such as cxas-scrapi), writing custom Python/TypeScript tool callbacks, and utilizing localized CLI workflows to programmatically structure, lint, test, and sync complex agent hierarchies. You will merge the speed of low-code visual canvas building with the absolute determinism of custom-coded logic.
What you'll be doing:
- Develop Multi-Agent Architectures: Build and configure modular, hierarchical agent networks (Root/Steering agents and targeted Sub-agents) using a combination of the CX Agent Studio canvas and programmatic Code Agents.
- Write Custom Code Tools & Callbacks: Program specialized backend logic, data transformation scripts, and custom tool callbacks in Python or TypeScript to extend agent capabilities beyond basic natural language prompts.
- Leverage GECX Engineering CLI & Tooling: Run automated code-first developer workflows utilizing uv environments and the cxas CLI for structural static linting (cxas lint) and advanced semantic instruction validation (cxas llm-lint).
- Design Generative Playbooks & Control Flows: Author and maintain structured, XML-like agent instructions (
, , ) that natively hook into custom Python tools ({@TOOL: custom_script}) and sub-agent routing syntax ({@AGENT: specialized_subagent}). - Program Enterprise Integrations: Seamlessly hook Code Agents into live databases, product catalogs, CRMs, and CCaaS networks (e.g., Genesys, Avaya) via Model Context Protocol (MCP) or secure OpenAPI webhooks.
- Automate Quality & Evaluation (CI/CD): Script programmatic, golden-scenario test cases and simulation evals using simulation frameworks to test multi-turn agent trajectories, preventing hallucinations and conversational regressions before sync-to-prod.
Skills and experience you will bring:
- Bachelor’s degree in computer science, engineering field, or equivalent practical experience.
- 3+ years of experience building conversational AI solutions, virtual agents, or programmatic AI workflows.
- Strong proficiency in Python or TypeScript/Node.js, with hands-on experience handling complex JSON payloads, RESTful APIs, and cloud-hosted webhooks.
- Experience utilizing Git-based developer workflows and command-line interfaces (CLIs) for software versioning and deployment.
- Hands-on experience building with Google’s GECX Code Agent tooling (e.g., cxas-scrapi workspace/SDK, Python-based agent foundries).
- Good technical understanding of Dialogflow CX, CX Agent Studio, or similar advanced, stateful conversational frameworks.
- Experience deploying streaming, low-latency audio-to-audio (A2A) voice agents and integrating with telephony (SIP/RTP) or CCaaS partner environments.
- Solid grasp of prompt engineering safety protocols, blocklists, and programmatic fallback behaviors (e.g., before_model_callback or after_tool_callback hooks).
- Experience with BigQuery or Google Cloud Logging to programmatically extract conversation traces, search text transcripts, and build data-driven performance metrics.