GEN AI Architect

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

• 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.