Gen AI Architect
Apply NowCompany: Omni Inclusive
Location: Orlando, FL 32828
Description:
Job Description:
- Lead the architectural design and implementation of scalable, generative AI-powered solutions for business automation, leveraging both Azure and Google Cloud platforms.
- Architect end-to-end AI model workflows, utilizing Azure AI, and Google AI tools. Focus will be on applications involving complex document intelligence, multi-modal data analysis, and advanced image processing tasks.
- Design and oversee the development of optimized RAG (Retrieval Augmented Generation) pipelines that incorporate varied data sources and formats to improve prompt execution.
- Establish best practices for prompt engineering and iterative refinement to maximize the accuracy and relevance of outputs across diverse data types.
- Collaborate with cross-functional teams (engineering, data science, business) to translate complex business requirements into robust, scalable AI component designs.
- Champion the integration of the client's proprietary generative AI tools into the architecture and development lifecycles.
- Direct the implementation of robust API management strategies using Apigee for secure and efficient access to AI models and related services.
- Ensure all solution designs adhere to stringent data governance policies and use cloud-native security mechanisms and compliance tools.
- Provide architectural guidance and design patterns for leveraging generative AI within critical business processes like License Audit and Product Approval, emphasizing scalable and verifiable outcomes.
- Establish and automate DevOps pipelines for model deployment, testing and iterative enhancements.
Skills:
- Deep expertise with Azure AI services (including Cognitive Services) and Google Cloud AIML platform.
- Extensive knowledge and practical experience with document processing using Azure Document Intelligence and alternative OCR technologies.
- Mastery of Snowflake for data modeling, warehousing, and integrating with advanced analytics workflows.
- Proficiency with cloud orchestration tools, like GKE Scheduler, and asynchronous communication services (e.g., Google PubSub).
- Advanced expertise in API management using Apigee and related security best practices.
- Proven ability to design and implement Kubernetes-based AI model deployments, including model optimization techniques.
- Strong command of Python for development and automation tasks.
- Demonstrated experience converting business needs into scalable and maintainable technical designs.
- Experience working with and extending custom Generative AI tooling.
- Deep understanding of Retrieval Augmented Generation (RAG) concepts and its applications.
- Lead the architectural design and implementation of scalable, generative AI-powered solutions for business automation, leveraging both Azure and Google Cloud platforms.
- Architect end-to-end AI model workflows, utilizing Azure AI, and Google AI tools. Focus will be on applications involving complex document intelligence, multi-modal data analysis, and advanced image processing tasks.
- Design and oversee the development of optimized RAG (Retrieval Augmented Generation) pipelines that incorporate varied data sources and formats to improve prompt execution.
- Establish best practices for prompt engineering and iterative refinement to maximize the accuracy and relevance of outputs across diverse data types.
- Collaborate with cross-functional teams (engineering, data science, business) to translate complex business requirements into robust, scalable AI component designs.
- Champion the integration of the client's proprietary generative AI tools into the architecture and development lifecycles.
- Direct the implementation of robust API management strategies using Apigee for secure and efficient access to AI models and related services.
- Ensure all solution designs adhere to stringent data governance policies and use cloud-native security mechanisms and compliance tools.
- Provide architectural guidance and design patterns for leveraging generative AI within critical business processes like License Audit and Product Approval, emphasizing scalable and verifiable outcomes.
- Establish and automate DevOps pipelines for model deployment, testing and iterative enhancements.
Skills:
- Deep expertise with Azure AI services (including Cognitive Services) and Google Cloud AIML platform.
- Extensive knowledge and practical experience with document processing using Azure Document Intelligence and alternative OCR technologies.
- Mastery of Snowflake for data modeling, warehousing, and integrating with advanced analytics workflows.
- Proficiency with cloud orchestration tools, like GKE Scheduler, and asynchronous communication services (e.g., Google PubSub).
- Advanced expertise in API management using Apigee and related security best practices.
- Proven ability to design and implement Kubernetes-based AI model deployments, including model optimization techniques.
- Strong command of Python for development and automation tasks.
- Demonstrated experience converting business needs into scalable and maintainable technical designs.
- Experience working with and extending custom Generative AI tooling.
- Deep understanding of Retrieval Augmented Generation (RAG) concepts and its applications.