Description

Architect and implement scalable generative AI solutions for business automation, focusing on document intelligence and multi-modal data analysis.

This role is on-site.

Responsibilities

• Design end-to-end AI model workflows using Azure AI and Google AI tools.
• Build optimized Retrieval Augmented Generation (RAG) pipelines integrating varied data sources.
• Manage API access to AI models using Apigee for secure deployment.
• Automate DevOps pipelines for model deployment, testing, and iterative enhancements.
• Translate business requirements into scalable AI component designs.

Required Skills

• 5+ years of experience in technical design and architecture.
• Deep expertise with Azure AI services (including Cognitive Services) and Google Cloud AI/ML platforms.
• Extensive experience with document processing using Azure Document Intelligence or alternative OCR technologies.
• Mastery of Snowflake for data modeling, warehousing, and analytics integration.
• Proficiency with cloud orchestration tools like GKE Scheduler and asynchronous services like Google Pub/Sub.
• Advanced expertise in API management using Apigee and related security best practices.
• Proven ability to design and implement Kubernetes-based AI model deployments and optimization techniques.
• Strong command of Python for development and automation.
• Deep understanding of Retrieval Augmented Generation (RAG) concepts and applications.

Preferred Skills

• Experience with iterative refinement of prompt engineering to improve output accuracy.

Key Skills

Education

Not specified