Role: Google Cloud AI Engineer for Partner Flex
Location: Remote
Role Overview
We are seeking a highly skilled Artificial Intelligence Engineer. This role is pivotal in
establishing Google's Data Cloud as the essential foundation for the "agentic era". You will
be responsible for designing and deploying sophisticated AI agents and grounding them
in unique business data to ensure trust and operational efficiency.
Core Responsibilities
Agentic Design & Implementation
• Develop intelligent agents using Vertex AI Agent Builder to automate complex
business workflows.
• Leverage the Agent Developer Kit ADK to build and manage multi-agent systems
that collaborate to solve end-to-end business challenges.
• Implement tools like MCP Model Context Protocol) Toolbox to securely connect
agents to enterprise databases like BigQuery and Spanner.
AI on Data Strategy
• Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless
integration with BigQuery for feature engineering.
• Build and optimize streaming data pipelines (e.g., via Dataflow) to execute
real-time inference using RunInference API or Vertex AI endpoints.
• Ground AI models in live business context using vector engines within BigQuery or
AlloyDB to eliminate "AI amnesia".
Operational Excellence (Soft Skills)
• Active Participation: Show up promptly for all internal and client-facing meetings.
• Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
• Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
• Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
• Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
• Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
• Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
• Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.
Preferred Experience
Background in financial services or retail to better understand industry-specific data logic (e.g., credit risk, royalty forecasting, or search relevance).
• Knowledge of privacy and compliance standards for handling PII through masking and redaction.