Sameeullah S.

About Sameeullah S.

Enterprise AI & GenAI Architecture leader with 18+ years of experience designing and delivering production-scale AI and cloud platforms on Microsoft Azure. I specialize in building enterprise GenAI and agentic AI systems that automate complex finance, tax, and compliance workflows with secure, governed, and scalable architectures.I lead architecture for multi-agent AI platforms, RAG-based document intelligence systems, and LLM-driven validation and automation pipelines. My work focuses on translating domain-heavy business processes into intelligent, reusable AI platforms with strong governance, auditability, and human-in-the-loop controls.At EY, I drive GenAI platform architecture and enterprise AI initiatives across large client programs — covering AI landing zones, agent orchestration, retrieval architectures, guardrails, and responsible AI design. I work closely with business, functional, and engineering leaders to align AI capabilities with measurable operational outcomes.My core areas of focus include:• Enterprise GenAI & Agentic AI Architecture• Multi-Agent Workflow Platforms• RAG & Intelligent Document Processing Systems• Azure OpenAI & AI Platform Architecture• AI Governance, Guardrails & Validation Frameworks• Finance, Tax & Compliance Automation• Architecture Standards & Technical Governance• Pre-sales AI Solutioning & Platform Strategy• Cross-team Architecture Leadership & MentoringActively contribute to architecture standards, reusable AI platform patterns, and governance frameworks that enable safe and scalable enterprise AI. adoption.Always open to conversations on enterprise GenAI platforms, agentic AI design, and AI architecture strategy.

Experience

1. Associate Director Senior Solution Architect Ai & Cloud Platforms

   EY

   Nov 2021 — Present · Mumbai, IN

   Lead architecture and delivery of enterprise AI and GenAI platforms enabling large-scale automation across Tax & Compliance workflows.Key contributions:Architected enterprise AI agent platform on Azure supporting multiple tax and compliance automation use casesDesigned production-grade GenAI and RAG platforms using Azure OpenAI, AI Search, Document Intelligence, and Azure MLBuilt multi-agent automation systems including:Trial Balance extraction & cleansing agentsChart of Accounts mapping agentsiXBRL compliance automation agentsAssisted financial review agentsCT transmittal automation agentsDesigned agentic workflows and LLM orchestration pipelines for intelligent document processing and validationImplemented RAG-based document analysis platforms with vector search and domain-aware retrievalDefined AI governance architecture including prompt controls, output validation, human-in-loop checkpoints, and auditabilityDesigned secure Azure landing zone and platform architecture for AI workloads (network isolation, private endpoints, guardrails)Established reusable AI architecture patterns and platform blueprints across teamsLead architecture reviews and technical governance forumsMentor architects and senior engineers on GenAI and platform architectureContribute to AI solutioning, estimation, and pre-sales architecture proposalsImpact:Reduced manual tax processing effort significantly through AI automationEnabled seconds-level document processing via AI extraction agentsImproved classification and compliance accuracy through ML + LLM hybrid modelsEstablished reusable enterprise AI agent architecture framework

Education

• IET Sitapur road lucknow

  Master, MCA

  2001 — 2006