Build and ship enterprise AI products by designing LLM coding-agent harnesses, evaluation benchmarks, and reliable production systems, while exploring model improvements and applied research.
Conversational AI Engineer - Google/GECX & Code Agents
๐ Description
- Build modular, hierarchical multi-agent applications using CX Agent Studio and Code Agents.
- Develop custom Python or TypeScript tools, callbacks, backend logic, and data transformations.
- Use GECX CLI workflows to lint, validate, test, and sync agent hierarchies.
- Author agent instructions, playbooks, and control flows for tool use and sub-agent routing.
- Integrate agents with databases, product catalogs, CRMs, and CCaaS platforms using MCP or OpenAPI webhooks.
- Automate scenario testing and simulation evaluations to identify hallucinations and conversational regressions.
๐ ๏ธ Requirements
- Bachelorโs 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 Googleโs 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.
Full job description
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:
- Bachelorโs 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 Googleโs 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.
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