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Google Cloud Platform Architect

HighbrowUnited States🇺🇸United StatesPosted 15 Sept 2026

Why This Role Stands Out

This remote opportunity as a Google Cloud Platform Architect at Highbrow offers incredible growth potential by allowing you to architect cutting-edge AI solutions using advanced tools like Claude code and Google Antigravity. You'll thrive here if you possess deep expertise in AI development and cloud platforms, and are eager to contribute to innovative projects within a flexible work environment.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
Yesterday
AWSMLOpsMachine LearningNLPAzureComplianceComputer VisionContinuous ImprovementGenerative AIGoogle Cloud

Job Description

Location: Remote

Key skills: Claude code, Google Antigravity, openai, Cursor, langchain, Autogen, Vector Databases

Job Description

  • Possess 12-15 years of progressive experience in architecting, designing, and implementing robust data and artificial intelligence solutions, specifically within the Google Cloud Platform ecosystem.
  • This role operates under a hybrid work model, requiring a blend of on-site collaboration and remote work to foster team synergy and project delivery efficiency.

 

Required Skills:

  • Demonstrated expertise in leveraging Claude code for advanced AI development, with a proven ability to integrate and optimize its capabilities within complex architectures.
  • Mandatory proficiency with Google Antigravity, showcasing a strong capability to design and implement solutions utilizing this critical platform component.
  • Extensive hands-on experience with OpenAI models, including their deployment, fine-tuning, and integration into enterprise-grade applications for diverse use cases.
  • Solid foundational understanding and practical application of Cursor for efficient code generation and development workflows in an AI-centric environment.
  • Proven ability to implement and manage solutions utilizing LangChain, demonstrating expertise in orchestrating complex language model applications and workflows.
  • Strong working knowledge and practical experience with Autogen, enabling the development of multi-agent conversational AI systems and automated task execution.
  • Proficiency in leveraging LlamaIndex for advanced data indexing and retrieval strategies, crucial for enhancing the performance of large language model applications.
  • Demonstrated capability in utilizing Semantic Kernel to build intelligent agents and integrate AI services seamlessly into existing applications and platforms.
  • Foundational understanding of MCP principles, reflecting a broad knowledge base in cloud and enterprise technologies.
  • Expertise in designing and implementing Retrieval Augmented Generation (RAG) architectures to improve the accuracy and relevance of AI model outputs by integrating external knowledge sources.
  • Comprehensive experience with various Vector Databases, including their selection, deployment, and optimization for efficient similarity search and AI data management.

 

Job Responsibilities

  • Lead the architectural design and implementation of scalable, secure, and high-performance data and AI solutions on Google Cloud Platform (Google Cloud Platform).
  • Drive the strategic vision for leveraging advanced AI/ML capabilities, including large language models and generative AI, within Google Cloud Platform environments.
  • Architect robust data pipelines and machine learning operationalization (MLOps) frameworks to support the full lifecycle of AI models.
  • Guide cross-functional teams in adopting best practices for Google Cloud Platform services, data governance, and AI solution development.
  • Oversee the integration of various AI tools and frameworks, such as Claude code, OpenAI models, LangChain, AutoGen, and LlamaIndex, into enterprise solutions.
  • Define technical standards and patterns for vector databases and Retrieval Augmented Generation (RAG) architectures to enhance AI model performance and relevance.
  • Mentor junior and mid-level architects and engineers, fostering their growth in Google Cloud Platform, data engineering, and AI/ML domains.
  • Ensure the security, compliance, and cost-effectiveness of all Google Cloud Platform-based data and AI infrastructure and applications.
  • Collaborate with product management and business stakeholders to translate complex requirements into actionable technical designs and roadmaps.
  • Evaluate emerging Google Cloud Platform services and AI technologies, recommending strategic adoption to maintain a competitive edge.
  • Establish comprehensive monitoring, logging, and alerting strategies for critical data and AI systems on Google Cloud Platform.
  • Drive continuous improvement initiatives for existing data platforms and AI models, focusing on performance, scalability, and reliability.
  • Manage the technical delivery of complex data and AI projects, ensuring alignment with architectural principles and business objectives.
  • Provide expert guidance on the selection and implementation of appropriate Google Cloud Platform services for data storage, processing, and AI model deployment.

Department/Project Description

Experience with specific industry verticals (e.g., finance, healthcare).

Knowledge of other cloud platforms (AWS, Azure) data and AI services.

Experience with MLOps tools and practices.

Experience with real-time data streaming and processing.

Experience with graph databases and graph analytics.

Experience with natural language processing (NLP) and computer vision.

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