GCP Architect; Data and AI background; Client

GCP Architect (Data and AI background) (Client: )

Location:

Remote

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

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.

• 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 Lang Chain, 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 Llama Index 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.

• Lead the architectural design and implementation of scalable, secure, and high‑performance data and AI solutions on Google Cloud Platform (GCP).
• Drive the strategic vision for leveraging advanced AI/ML capabilities, including large language models and generative AI, within GCP 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 GCP services, data governance, and AI solution development.
• Oversee the integration of various AI tools and frameworks, such as Claude code, OpenAI models, Lang Chain, Auto Gen, and Llama Index, 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 GCP, data engineering, and AI/ML domains.
• Ensure the security, compliance, and cost‑effectiveness of all GCP‑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 GCP 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 GCP.
• 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 GCP services for data storage, processing, and AI model deployment.

• 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.