Need Min 13+ years with a valid Linkedin
Google Cloud AI Engineer
US Remote PST time zone
Contract
Note : In addition to the JD requirements, the candidate should be comfortable with Terraforms and DevOps work on Google Cloud Platform.
Job Description :
Google Cloud AI Engineer (Partner Flex)
Role Overview
We are seeking a highly skilled Artificial Intelligence Engineer to help establish Google's Data Cloud as a critical foundation for the agentic era. This role will focus on designing, developing, and deploying sophisticated AI agents grounded in enterprise business data to deliver trustworthy, production-ready AI solutions.
Core Responsibilities
Agentic AI Design & Implementation
- Develop intelligent AI agents using Vertex AI Agent Builder to automate complex business workflows.
- Build and manage multi-agent systems using the Agent Development Kit (ADK).
- Implement Model Context Protocol (MCP) and related tooling to securely connect AI agents with enterprise data sources such as BigQuery and Spanner.
- Design agent orchestration, tool usage, state management, and multi-step reasoning workflows.
AI on Data Strategy
- Train, tune, evaluate, and deploy AI models using Vertex AI.
- Integrate AI solutions with BigQuery for feature engineering and business data access.
- Develop streaming data pipelines using Dataflow.
- Support real-time inference using the RunInference API and Vertex AI Endpoints.
- Implement vector-based retrieval using BigQuery Vector Search and AlloyDB Vector Engine.
- Ground LLMs and AI agents in live enterprise data to improve accuracy, relevance, and reliability.
Operational Excellence
- Participate actively and consistently in project meetings and technical discussions.
- Provide structured status updates regarding milestones, progress, dependencies, and technical blockers.
- Collaborate proactively with engineering, data, product, and architecture teams.
- Escalate technical issues appropriately and contribute to collaborative troubleshooting.
- Translate high-level business requirements into scalable and robust AI architectures.
Required Technical Skills
Google Cloud AI
- Vertex AI
- Vertex AI Agent Builder
- Vertex AI Pipelines
- Model Garden
- Vertex AI Endpoints
- Model Evaluation
Agentic AI
- Agent Development Kit (ADK)
- Multi-Agent Systems
- AI Agents
- Model Context Protocol (MCP)
- Tool Calling
- Agent Orchestration
Data Engineering
- BigQuery
- Spanner
- Dataflow
- SQL
- Python
- Feature Engineering
- Data preprocessing, including:
- Scaling
- Encoding
- Imputation
Google Cloud Infrastructure
- Google Cloud Storage (GCS)
- Vertex AI Endpoints
- Production cloud deployments
- Secure integration with enterprise data platforms
Emerging Technologies
Experience with:
- Stateful real-time processing
- Modern agentic AI architectures
- Production-grade LLM systems
- Real-time inference
- Vector search and retrieval-augmented generation
Preferred Experience
Experience in industries such as:
- Financial Services
- Credit Risk
- AML/KYC
- Financial Analytics
- Retail
- Search Relevance
- Recommendation Systems
- Forecasting
Security & Compliance
Experience with:
- PII masking
- Data redaction
- Privacy controls
- Enterprise compliance standards
- Secure handling of sensitive data
Ideal Candidate Profile
The ideal candidate will have:
- Strong hands-on experience with Google Cloud Vertex AI
- Experience building production AI agents
- Knowledge of multi-agent architectures
- Expertise in BigQuery and enterprise data engineering
- Strong Python and SQL proficiency
- Experience deploying production LLM applications
- Strong communication and cross-functional collaboration skills
- Ability to translate business requirements into scalable AI solutions
- Experience working with modern agentic frameworks and enterprise data platforms
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