Google Cloud AI Engineer
Artificial Intelligence
Big Data
Bigquery
Cloud
Cloud Native
Cloud Platform
Cloud Platforms
Data Analysis
Data Analytics
Data Engineer
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Databases
Generative Ai Platform
Google Cloud
Google Cloud Dataflow
Google Cloud Platform
Google Cloud Spanner
Google Vertex Ai
Information Technology (IT)
Machine Learning
Programming
SQL
Vertex Ai
Vertex Ai Agents
Job Description
Altimetrik Corp is seeking a Google Cloud AI Engineer to design and deploy AI agents grounded in unique business data as part of Google’s Data Cloud for the agentic era. This role blends agentic design with AI-on-data strategy, with a strong focus on real-time inference, secure data grounding, and turning high-level business goals into robust technical architectures.
What you’ll be doing
- Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows.
- Use the Agent Developer Kit (ADK) to build and manage multi-agent systems that collaborate to address end-to-end business challenges.
- Integrate tools such as MCP (Model Context Protocol) Toolbox to securely connect agents to enterprise databases including BigQuery and Spanner.
- Use Vertex AI for model training, tuning, and deployment, ensuring smooth integration with BigQuery for feature engineering.
- Build and optimize streaming data pipelines (for example, via Dataflow) to support real-time inference using RunInference API or Vertex AI endpoints.
- Ground models in live business context by leveraging vector engines within BigQuery or AlloyDB to reduce “AI amnesia”.
- Attend internal and client-facing meetings promptly, and deliver regular, structured status updates on milestones and technical blockers.
- Request help when facing technical hurdles and contribute to a collaborative troubleshooting environment.
What you bring
- 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 including scaling, encoding, and imputation.
- Hands-on experience with Google Cloud Storage and Vertex AI endpoints.
- Familiarity with stateful real-time processing and recent innovations in agentic architectures.
Helpful background
- Experience in financial services or retail to support industry-specific data logic (for example, credit risk, royalty forecasting, or search relevance).
- Knowledge of privacy and compliance practices for handling PII using masking and redaction.
Benefits
- 401(k)
- Health insurance
Location and travel
Location: Remote
Travel: 25% (Required)
Application check
Willingness to complete a pre-employment background check contingent upon an offer.
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