Gen AI Lead Developer

As an AI Architect you will own the end-to-end architecture, design and lead delivery of enterprise-grade AI solutions across generative AI domains such as document processing, language, vision, and agentic (LLM-based) systems on cloud platforms preferably Azure. You will partner with customer stakeholders to translate business goals into robust, secure, and cost effective architectures , lead engineering teams and establish MLOps, governance and responsible-AI practices. The role requires deep hands-on experience with Azure AI services (and complementary cloud technologies), practical knowledge of document processing use-cases, and expertise building RAG, LLM verification, and multi-agent solutions.

Core responsibilities

1. Solution Architecture & Design

Design end-to-end pipelines

ingestion, pre-processing, OCR/layout analysis, extraction, normalization, reconciliation, validation, and human-in-the-loop.

• Translate business problems (document extraction, contract analytics, claims processing, knowledge bases, chat assistants) into measurable ML objectives and architecture blueprints.
• Facilitate stakeholder workshops (Jira/Confluence/Miro) to capture success criteria, SLAs and compliance requirements.
• Architect hybrid solutions combining Azure Cognitive APIs, custom ML models, Azure OpenAI/LLMs and RAG to balance accuracy, latency and cost.
• Define API/integration patterns (REST), event-driven messaging and connectors to Kafka systems. 2. Agentic & Generative AI Design
• Design RAG workflows with embeddings and vector search for source-cited responses and hallucination mitigation.
• Design and advise on agentic AI frameworks (multi-agent roles, tool-invocation patterns, context/state management) for autonomous or semi-autonomous assistants.
• Specify MCP/server orchestration approaches (stateful context, plugin/tool integrations, secure communications).