Note: The job is a remote job and is open to candidates in USA. Altimetrik is seeking a highly skilled Artificial Intelligence Engineer to establish Googleʼs Data Cloud as the foundation for the 'agentic era'. The role involves designing and deploying sophisticated AI agents, ensuring trust and operational efficiency by grounding them in unique business data.
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 like 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
Skills
- 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
- 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
- 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
- Willingness to travel: 25% (Required)
- 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
Benefits
- 401(k)
- Health insurance
Company Overview
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