Role: GCP Architect (Data and AI background)
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.
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 (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, 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 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.
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.