GCP Architect/GCP Data Architect
VDart, Inc.
Charlotte, NC, United States
2 months ago
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Role details
Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$228,800.0
Working hours
Regular working hours
Job source
Tech stack
Clean Code Principles
Artificial Intelligence
Information Engineering
Data Governance
Cursor (Graphical User Interface Elements)
DevOps
Machine Learning
TypeScript
Data Logging
Google Cloud
Enterprise Software Applications
Data Storage Technologies
+8 more
Large Language Models
Multi-Agent Systems
Generative AI
AI Platforms
Data Management
Machine Learning Operations
Virtual Agents
Data Pipelines
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., * 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., Role Overview: As a Senior Full-Stack Engineer specializing in TypeScript, you will play a pivotal role in designing and developing robust, scalable web applications. This positio…
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Requirements
- 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 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.
Benefits & conditions
- $130.00 per hour
About the company
SaidGig
- Charlotte, NC
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$110.00 per hour As a Backend Engineer, you will play a crucial role in shaping the future of AI systems by developing scalable backend services and APIs that enhance model performance. Your expert…
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