Google Cloud AI Engineer - USA, Remote [PST] : Contract

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