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Job Description

  • Architect enterprise-scale, production-ready Data-to-AI platforms, advanced Retrieval-Augmented Generation (RAG) pipelines, semantic knowledge graphs, and vector databases using Vertex AI Vector Search to support scalable generative AI applications.
  • Lead end-to-end implementation of Google Cloud data platforms using BigQuery, Dataflow, Pub/Sub, and AlloyDB, building high-throughput batch and streaming pipelines that optimize complex query performance.
  • Design, build, and deploy autonomous AI agents and multi-agent coordination systems by leveraging the Vertex AI Agent Ecosystem, Reasoning Engine, and the comprehensive Gemini foundation model family.
  • Implement agentic reasoning loops, memory systems, tool and API integrations, and robust AgentOps frameworks for continuous monitoring, tracing, evaluation, fine-tuning, latency optimization, cost control, and safety compliance.
  • Advise executive stakeholders on generative AI transformation, lead technical scoping and rapid prototyping workshops, and mentor engineering teams in modern Google Cloud Data and AI system architectures.

Minimum qualifications:

  • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  • 5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment.
  • Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider.
  • Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures.
  • Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions.

Preferred qualifications:

  • Experience with CI/CD, IaC (Terraform), containers (Docker, GKE, Cloud Run), and agent evaluation/tracing.
  • Expertise designing autonomous multi-agent frameworks, cognitive workflows, and orchestrators (Vertex AI Agent Builder, Gemini Enterprise).
  • Proficient across Google Cloud data/AI services (Vertex AI, BigQuery, Dataflow, Spanner, Firestore, Vector Search).
  • Proven stakeholder management, advising C-level leaders, facilitating architecture workshops, and driving client enablement.
  • Track record leading delivery teams, architecting enterprise software, and executing cloud modernizations.
  • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  • 5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment.
  • Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider.
  • Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures.
  • Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions.
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Google
AI Research Lab · 500+ Members · Mountain View, CA, United States

Google builds internet, software, cloud, and AI products used by consumers, developers, and organizations. Its portfolio includes Search, YouTube, Android, Chrome, Maps, Gmail, Workspace, Google Cloud, advertising platforms, devices, and Gemini AI products. The company develops large-scale computing infrastructure and research that power information retrieval, communication, productivity, media, navigation, and machine learning. Google is the largest operating business within Alphabet and earns a substantial share of its revenue from digital advertising.

All jobs at Google

Location

United States

Job Overview
Job Posted:
2 weeks ago
Workplace
On-site
Job Type
Full Time
Education
Any
Experience
3+ years

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