Job Summary
We are seeking an experienced AI Architect to lead the design and delivery of enterprise-scale Agentic AI and Document Intelligence solutions. The ideal candidate will have hands-on experience building production-grade multi-agent systems, GenAI applications, and intelligent document processing platforms using Azure AI services and modern AI orchestration frameworks.
Key Responsibilities
- Architect and deliver enterprise Agentic AI solutions leveraging LLMs, RAG, and multi-agent frameworks.
- Design document intelligence platforms for document ingestion, classification, extraction, validation, summarization, and workflow automation.
- Build agent-based workflows for contract analysis, invoice processing, compliance review, and knowledge management.
- Develop scalable RAG architectures using vector databases, Azure AI Search, and knowledge repositories.
- Establish AI governance, security, observability, and responsible AI practices.
- Collaborate with business and engineering teams to drive AI transformation initiatives.
Skill Requirements
Required Skills & Experience
- 10+ years in software architecture and engineering.
- 3+ years of hands-on experience delivering production Agentic AI solutions.
- Experience with Agentic Document Intelligence/Intelligent Document Processing (IDP) at enterprise scale.
- Strong expertise in Azure OpenAI, Azure AI Foundry, Azure AI Document Intelligence, Azure AI Search.
- Hands-on experience with LangGraph, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex.
- Deep understanding of RAG, vector databases, prompt engineering, agent orchestration, and AI governance.
- Strong Python and cloud-native architecture experience.
Preferred
- Experience with MCP, Microsoft 365 Copilot, Copilot Studio, and Power Platform.
- Experience in legal, financial, insurance, healthcare, or procurement document automation.
- Azure AI and Architect certifications.
Ideal Candidate: Proven track record of designing and deploying autonomous AI agents and document intelligence solutions that deliver measurable business outcomes in production environments.