GCP Architect

Required Skills:

• 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.

• 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.