Cognitive Engineer

This pivotal role will be responsible for defining the technical vision, designing robust solutions with a primary focus on CCAI Agent Assist and Dialogflow CX.  This pivotal role will be responsible for defining the technical vision, designing robust solutions, and leading the end-to-end development of Google Contact Center AI (CCAI) initiatives, with a primary focus on CCAI Agent Assist, Agentic AI, Gen AI and Dialogflow CX.

 

Python 

•    Python Programming (Advanced): SCRAPI is a Python-based API. You must be proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns.

•    Environment & Dependency Management: Familiarity with modern Python package managers like uv, virtual environments (.venv), and pip.

•    Command Line Interface (CLI) Proficiency: Ability to navigate CLI tools, as well as general shell scripting

Conversational AI / Agent Architecture

•    Generative Agent Design: Shifting from legacy intent-based state machines to generative, goal-oriented architectures (understanding Apps, Agents, Sub-agents, and Sessions within CX Agent Studio).

•    Prompt Engineering & Context Management: Writing robust system instructions, managing conversational memory, and optimizing LLM context windows for voice interactions.

•    Dialogflow CX Fundamentals: Understanding the underlying mechanics of Dialogflow CX,

Google Cloud Platform(GCP)

•    Cloud Compute & Serverless: Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run.

•    gcloud CLI Mastery: Utilizing gcloud for project configuration and authenticating environments via application-default credentials.

API Integration & Tool Building

•    Tool Calling / Function Calling: Designing and registering external APIs ("Tools") that the LLM can invoke to retrieve data, execute backend tasks, or interact with external services.

•    Data Handling & Payload Parsing: Using utility functions to handle pagination, flatten API responses, and convert complex Protocol Buffers (Protos) into usable data.

Testing, Evaluation & CI/CD

•    Automated Agent Evaluation (Evals): Creating and orchestrating "Golden tests" and automated simulation runs using SCRAPI’s evals module.

•    Performance Metrics Tracking: Extracting, analyzing, and optimizing agent performance metrics (like real-time latency), which is highly critical for voice voice interactions.

•    Agentic IDE workflows: Using LLM-assisted development tools (like Gemini CLI or Claude Code) as integrated into the SCRAPI workflow to speed up agent scaffolding and debugging.

Bachelor Degree in relevant field with 4 years of relevant experience