100% Remote - AI Engineer (Vertex AI)

Summary: The AI Engineer (SCE) role focuses on developing intelligent agents and optimizing data strategies using Vertex AI to automate business workflows. The position requires collaboration with multi-agent systems and the implementation of tools for secure data connections. The engineer will also be responsible for real-time data processing and ensuring AI models are grounded in live business contexts. This is a fully remote position for a contract duration of over 12 months.

Key Responsibilities:

• 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 such as BigQuery and Spanner.
• 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".
• Show up promptly for all internal and client-facing meetings.
• Provide regular, structured status updates to team members and stakeholders regarding project milestones and technical blockers.
• Demonstrate the ability to ask for help when facing technical hurdles and contribute to a collaborative troubleshooting environment.
• Navigate corporate environments to translate high-level business goals into robust technical architectures.
• Proven experience with Model Garden, Vertex AI Pipelines, and model evaluation.
• Advanced knowledge of SQL for BigQuery, Python for ML engineering, and data preprocessing techniques (scaling, encoding, imputation).
• Hands-on experience with Google Cloud Storage and Vertex AI endpoints.
• Familiarity with stateful real-time processing and the latest innovations in agentic architectures.
• 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.

Key Skills:

• 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.
• 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.

Salary (Rate): undetermined

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT