A. Ahmed

AI & LLM Engineer

Softline Tech • Temps plein

Jul 2025 - Jul 2026 • 1 yr

Led the design, development, and deployment of 13+ production AI products, 30+ LangGraph AI agents, and 150+ REST APIs, serving 500–1,500 users across multi-tenant SaaS platforms. Architected scalable Agentic AI systems, multi-agent orchestration, RAG pipelines, AI microservices, and asynchronous task processing using LangGraph, FastAPI, Docker, Celery, Redis, PostgreSQL, MongoDB, Pinecone, FAISS, ChromaDB, Socket.IO, and JWT. Developed AI solutions spanning multi-tenant RAG SaaS, KYC compliance, fundraising automation, travel assistants, medical literature screening, workforce analytics, VC research, memo summarization, employee planning, real estate intelligence, animation labeling, and conversational PDF search. Fine-tuned and deployed Llama 2 (QLoRA), TinyLlama, and Stable Diffusion LoRA, serving production inference through vLLM, Ollama, Hugging Face, and commercial LLM APIs while reducing inference costs by 40–60%. Integrated OCR, Computer Vision, Whisper ASR, browser automation, semantic search, and multi-provider LLMs including OpenAI, Anthropic, Gemini, and Cohere into production workflows. Owned the complete SDLC, including solution architecture, implementation, testing, Docker deployment, production integration, technical documentation, and mentoring engineers. Key Achievements - Delivered 13+ production AI applications and 30+ autonomous AI agents. - Reduced document review time by 80%. - Accelerated medical research workflows by 95%. - Improved automated report generation by 85%. - Reduced planning cycles by 75%. - Automated outreach creation, cutting preparation time by 90%. - Reduced support tickets by 30% through AI automation. - Improved RAG retrieval relevance by 20%. - Achieved 85% meeting intent classification accuracy. - Delivered 95%+ face-matching accuracy for AI-powered KYC verification.

AI Instructor

Fiverr • Freelance

Jun 2025 - Feb 2026 • 8 mos

Delivered live online AI training to students across the United States, providing structured instruction from foundational Artificial Intelligence concepts to advanced Generative AI development. Designed hands-on learning experiences covering Data Analysis, Machine Learning, Deep Learning, Computer Vision, NLP, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern AI engineering workflows. Created practical AI lessons, coding exercises, and project-based assignments using Python and industry-standard AI frameworks, helping students understand real-world AI development practices. Guided learners through model development, experimentation, deployment concepts, and emerging Generative AI technologies. Key Achievements - Trained multiple student cohorts in practical AI development and applied machine learning. - Delivered end-to-end AI education covering the complete pipeline from data analysis to Generative AI systems. - Helped students build real-world AI projects and strengthen industry-relevant technical skills. - Simplified complex AI concepts into engaging, practical, and hands-on learning experiences.

AI & ML Engineer

AI Medical Technology • Temps partiel

Jun 2024 - Jun 2025 • 1 yr

Designed, developed, and deployed production-grade Machine Learning, Deep Learning, Computer Vision, and Generative AI solutions for enterprise clients. Built scalable AI applications, autonomous agents, and intelligent automation systems using LangChain, LangGraph, FastAPI, Docker, PyTorch, TensorFlow, Scikit-learn, PostgreSQL, Redis, and vector databases, delivering production-ready solutions across multiple industries. Developed end-to-end ML pipelines covering EDA, feature engineering, PCA, target encoding, outlier handling, imputation, model training, evaluation, and deployment. Architected and optimized CNNs, RNNs, LSTMs, Transformers, GANs, and classical ML models for predictive analytics, computer vision, NLP, and business intelligence applications. Built LLM-powered chatbots, RAG systems, and autonomous AI agents using LangChain and LangGraph, integrating OpenAI, Llama, Whisper, OCR, semantic search, browser automation, and Model Context Protocol (MCP) to automate complex enterprise workflows. Developed scalable AI microservices and REST APIs using FastAPI, enabling secure production deployment and seamless integration with existing business systems. Key Achievements - Delivered production AI, ML, and Generative AI solutions for enterprise clients across multiple industries. - Built autonomous AI agents and intelligent workflow automation systems using LangGraph. - Developed reusable AI tools and production APIs, accelerating enterprise AI integration. - Designed high-performance ML pipelines that improved model accuracy, scalability, and maintainability. - Successfully deployed AI applications from research to production, owning the complete development lifecycle.