Title : GEN AI Architect
Location : Charlotte, North Carolina (onsite)
GC ONLY
If you haven’t submit HCL Before Please share it.
|
Job Description (Posting). |
: · 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. |