Abdelrahman O.

I'm an AI engineer with 7 years of production experience at Microsoft Copilot and IBM, plus a Master's in AI and Data Science. I specialize in building agentic AI systems—intelligent, autonomous workflows that reason, act, and deliver measurable business outcomes. What most teams miss: AI isn't about the LLM, it's about orchestration. I design and deploy multi-agent systems using LangGraph, AutoGen, and production frameworks where AI agents collaborate with deterministic logic and human oversight to solve complex, high-stakes problems. I build systems that work, not demos that impress. EXPERTISE AGENTIC AI AND MULTI-AGENT SYSTEMS - Multi-agent orchestration (LangGraph, AutoGen, Crew.ai) - Agent design: perception, reasoning, action loops - State machines and supervisory control - Human-in-the-loop AI workflows - Agent-to-agent communication and collaboration - Real-time monitoring and agent auditing LARGE LANGUAGE MODELS AND LLM ENGINEERING - Prompt engineering and few-shot learning - Structured outputs (JSON schemas, Pydantic validation) - Function calling and tool use - Long-context reasoning (200+ page document analysis) - Fine-tuning and adaptation - Cost optimization and latency reduction - Multimodal LLMs (text + vision) RETRIEVAL-AUGMENTED GENERATION (RAG) AT SCALE - Hybrid vector + keyword indexing (Weaviate, Qdrant, Pinecone) - Query routing and intelligent retrieval - Chunk optimization and reranking - Context compression - Citation and source tracking - Conflict detection across document sets - Production RAG pipelines (reducing hallucination) PRODUCTION AI ARCHITECTURE - API-first design (FastAPI, serverless) - Microservices and distributed agent systems - Async processing and queue management - Model deployment and inference optimization - Monitoring, observability, logging - Graceful degradation and fallback strategies - Security and governance in regulated environments MACHINE LEARNING AND DATA SCIENCE - Supervised and unsupervised learning (XGBoost, Random Forest, ensemble methods) - Deep learning (CNN, RNN, Transformers, TensorFlow, PyTorch) - NLP pipelines (tokenization, embeddings, semantic search) - Statistical analysis and hypothesis testing - Data visualization and reporting WHAT I BUILD INTELLIGENT AGENTS AND CHATBOTS Agentic chatbots that reason through multi-step problems, retrieve relevant context, and execute actions. Customer support, technical assistance, content generation, decision support. DOCUMENT INTELLIGENCE SYSTEMS Multi-agent workflows that ingest complex document sets, extract structured information, detect conflicts, generate RFIs, build takeoffs, and produce cost estimates. Built for real-world accuracy, not demos. AUTONOMOUS WORKFLOWS AI agents that coordinate across business processes: data pipeline orchestration, content generation at scale, financial analysis, project management, research and analysis. RAG-POWERED ANALYTICS Question-answering systems over your proprietary data (documents, databases, knowledge bases) with source attribution, confidence scoring, and multi-turn reasoning. CUSTOM AI SOLUTIONS Tailored agentic systems for your specific workflow—whether that's construction estimating, contract review, healthcare intake, anomaly detection, or predictive analysis. TECHNICAL STACK Frameworks and Orchestration: LangGraph, AutoGen, Crew.ai, LangChain, LlamaIndex LLM Providers: OpenAI (GPT-4, GPT-4o), Anthropic Claude, open-source (Llama, Mistral) Vector Databases: Weaviate, Qdrant, Pinecone, Chroma Backend and Deployment: Python, FastAPI, Docker, AWS (SageMaker, Lambda, S3), serverless ML Frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost Data and Databases: SQL, PostgreSQL, MongoDB, BigQuery Monitoring and Observability: LangSmith, custom logging, performance tracking INDUSTRIES AND IMPACT Enterprise SaaS | Financial Services | Healthcare and Biotech | Construction and AEC | Legal Tech | Government and Defense | Consulting | E-commerce | Nonprofits --- HOW I WORK Discovery First — 20-minute conversation to understand your problem, timeline, and success metrics. No fluff, just clarity. Phased Delivery — Start with an MVP that proves value. Expand from there. You control scope at each phase. Production-Grade from Day One — Every system is built to scale, monitor, and evolve. Not a prototype. Transparent and Collaborative — Regular updates, explainable decisions, alignment on progress. I work with your timezone. Honest Assessment — Sometimes the answer isn't "build an AI agent." I'll tell you if a simpler solution fits better. LET'S TALK Whether you're exploring agentic AI for the first time or optimizing an existing system, let's have a conversation. Message me or schedule a consultation. I'm here to turn your business challenge into an intelligent, auto