Senior Gen AI Architect: RAG, Multimodal AI, Cloud

TechDigital Group; Charlotte (NC); On-site; USD 150,000 - 210,000; Full time

Job summary

TechDigital Group in Charlotte is seeking a Senior AI Architect to lead the design of scalable, generative AI-powered solutions across Azure and Google Cloud. You will architect end-to-end model workflows for complex document intelligence and multi-modal analytics, and optimize RAG pipelines with diverse data sources.

You will drive best practices in prompt engineering, collaborate with cross-functional teams, and ensure secure API access via Apigee while upholding data governance and DevOps

Qualifications

• Deep expertise across Azure AI services and Google Cloud AIML platforms.
• Proven document processing experience using Azure Document Intelligence or OCR tech.
• Strong Snowflake data modeling and analytics integration skills.

Responsibilities

• Lead design and implementation of scalable, generative AI-powered solutions on Azure and Google Cloud.
• Architect end-to-end AI model workflows for document intelligence and multi-modal data analysis.
• Design RAG pipelines using diverse data sources to improve prompt execution.
• Establish prompt engineering best practices for accurate outputs across data types.
• Collaborate with engineering, data science, and business teams to translate requirements into scalable designs.
• Integrate client proprietary generative AI tools into architecture lifecycles.
• Direct API management strategies via Apigee for secure AI access.
• Ensure designs meet data governance and cloud-security standards.
• Provide patterns for leveraging generative AI in critical business processes like License Audit and Product Approval.
• Automate DevOps pipelines for model deployment, testing, and iterative improvements.

Skills

Azure AI services

Google Cloud AIML

Document processing

Snowflake

GKE Scheduler

Google Pub/Sub

Apigee API management

Kubernetes deployments

Python

DevOps pipelines

RAG concepts

Data governance

OCR technologies

Security best practices

API security

Tools

Azure Document Intelligence

Google Pub/Sub

Apigee

Kubernetes

GKE Scheduler

Job description

Skill	Years of Exp	Proficiency Level (1-5)
Usage of LLM from OpenAI /any platform related to images or large data
Deep understanding of Retrieval Augmented Generation (RAG) concepts and its usages
Strong command of Python for development of automation tasks and integration API
Advanced expertise in API management using Apigee and related security best practices
Experience working with and extending any Generative AI tooling
Working knowledge of AIML platform like Azure AI services and Google Cloud AIML

Responsibilities:

• 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.