Gen AI Architect
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Job Location:
Jersey, NJ - USA
Monthly Salary:
Not Disclosed
Posted on:
8 hours ago
Vacancies:
1 Vacancy
Job Summary
Location - NJ - onsite
Job Description
Responsibilities:
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Lead the architectural design and implementation of scalable generative AI-powered solutions for business automation leveraging both Azure and Google Cloud platforms.
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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.
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Design and oversee the development of optimized RAG (Retrieval Augmented Generation) pipelines that incorporate varied data sources and formats to improve prompt execution.
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Establish best practices for prompt engineering and iterative refinement to maximize the accuracy and relevance of outputs across diverse data types.
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Collaborate with cross-functional teams (engineering data science business) to translate complex business requirements into robust scalable AI component designs.
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Champion the integration of the clients proprietary generative AI tools into the architecture and development lifecycles.
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Direct the implementation of robust API management strategies using Apigee for secure and efficient access to AI models and related services.
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Ensure all solution designs adhere to stringent data governance policies and use cloud-native security mechanisms and compliance tools.
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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.
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Establish and automate DevOps pipelines for model deployment testing and iterative enhancements.
Skills:
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Deep expertise with Azure AI services (including Cognitive Services) and Google Cloud AIML platform.
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Extensive knowledge and practical experience with document processing using Azure Document Intelligence and alternative OCR technologies.
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Mastery of Snowflake for data modeling warehousing and integrating with advanced analytics workflows.
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Proficiency with cloud orchestration tools like GKE Scheduler and asynchronous communication services (e.g. Google PubSub).
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Advanced expertise in API management using Apigee and related security best practices.
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Proven ability to design and implement Kubernetes-based AI model deployments including model optimization techniques.
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Strong command of Python for development and automation tasks.
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Demonstrated experience converting business needs into scalable and maintainable technical designs.
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Experience working with and extending custom Generative AI tooling.
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Deep understanding of Retrieval Augmented Generation (RAG) concepts and its applications.
Key Skills
- APIs
- Pegasystems
- Spring
- SOAP
- .NET
- Hybris
- Solution Architecture
- Service-Oriented Architecture
- Adobe Experience Manager
- J2EE
- Java
- Oracle
