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Most data problems show up the same way, whether it's a spreadsheet someone updates by hand every week or a pipeline that's quietly started giving numbers nobody trusts. I build and fix ETL pipelines, warehouses, and API integrations on GCP and AWS, from replacing manual copy-paste with automated pulls to saving a client thousands a month just by cleaning up how their data was stored. Tell me what's manual or what feels off, and I'll give you a straight read on what it'll take to fix it. No sales pitch, just the actual diagnosis. Over the last 3 years I've delivered 55+ data projects across finance, healthcare, energy, and e-commerce, from one-off ETL jobs to platforms processing billions of records a day. I work GCP-first (BigQuery, Airflow, dbt, Dataflow), and I'm comfortable across AWS, Postgres, and the messy real-world stack most teams actually have. What I build: - End-to-end ETL/ELT pipelines in Python, SQL, Airflow, and dbt - BigQuery / Snowflake / Redshift warehouses and data models that stay clean as they grow - Migrations off legacy jobs and on-prem databases — without losing data in the move - Metabase, Looker Studio, and Power BI dashboards your team will actually open - Query and cost optimization when your warehouse bill stops making sense - API integrations with proper logging, retries, and checkpoints, so failures are visible instead of silent You probably need me if: - Your pipelines break and you hear it from a stakeholder, not an alert - Reports run slow, cost too much, or quietly disagree with each other - A previous developer left and nobody fully understands the setup anymore - You're scaling fast and the current data stack is starting to crack A few real results: - Architected pipelines processing 5B+ records daily at 99% reliability - Cut a client's warehouse costs ~50% by migrating legacy jobs to BigQuery - 4× throughput and 70% faster ingestion on an API pipeline pulling 2K+ domains a day - 40% faster pipeline runs through Airflow optimization How I work: a clear yes/no on feasibility before you commit, regular updates, and no disappearing mid-project. Most clients come back — usually because fixing one thing surfaces the next. If that sounds like your situation, send a short note on what's breaking or what you're trying to build, and I'll tell you straight what it'll take.

Need to automate a repetitive business process or build an AI-powered workflow? I can help you turn it into a reliable, practical solution using AI, Python, APIs, and automation. I build AI-powered automation systems that turn messy data into decisions—and decisions into automated actions. Whether you need a lead-generation system that runs on autopilot, an AI agent that understands your documents, a Python data pipeline, or an automation workflow connecting your tools and data, I build systems designed to work with real-world data and real business processes. Hi, I'm Ibad Ahmed, an AI Automation Engineer specializing in n8n, Python, AI agents, RAG systems, and data-driven automation. I help startups, SaaS companies, and growing businesses automate repetitive processes, extract value from messy data, and connect AI directly to the workflows they already use. My focus is on building practical, reliable systems—not proof-of-concept demos that stop working when real data enters the system. WHAT I BUILD AI Automation & Workflow Systems End-to-end n8n workflows that collect data, process it, use AI for reasoning, and automatically trigger the next action. AI Agents & RAG Systems AI agents that work with your documents and business data, using retrieval and structured context to provide grounded, useful answers. Python & Data Pipelines Custom Python scripts, data extraction, cleaning, transformation, backend logic, and automation when a workflow needs more than a no-code solution. API & Business Integrations Connecting tools such as Google Sheets, CRMs, Gmail, WhatsApp, AI APIs, databases, and other services into one automated workflow. WHAT I BRING Hands-on n8n experience across scraping, AI reasoning, and multi-step workflows Experience building RAG-based AI agents grounded in real documents and data End-to-end automation pipelines from data collection → processing → AI scoring → automated action Strong Python and SQL skills for custom logic, data processing, and integrations Ability to take ownership of a project from workflow design through implementation and testing A data-science background that helps me work with messy, unstructured, and real-world data TOOLS & TECHNOLOGIES Automation: n8n, Workflow Automation Programming: Python, SQL AI: OpenAI, Groq, LLM APIs, Prompt Engineering, AI Agents RAG: Pinecone, Vector Databases, Retrieval-Augmented Generation Data: Data Cleaning, Data Modeling, Web Scraping Integrations: Google Sheets, Google Workspace APIs, REST APIs My process starts with understanding the business problem, not just the tools you think you need. I'll map the workflow, identify what should be automated, build the system, test it against real-world data, and deliver something you can actually use day-to-day. If you have a repetitive process, messy dataset, AI idea, or workflow that needs to run without constant manual work, send me the details. I'll help you figure out the most practical way to automate it.

Stop building just another feature. Start automating business outcomes. As a Top-Rated Full-Stack Engineer (100% Job Success) specializing in AI Automation, I bridge the gap between traditional MERN/Next.js development and cutting-edge LLM integration. I don’t just wrap APIs; I build secure, production-grade AI systems that save time, cut costs, and scale gracefully. WHY PARTNER WITH ME? 🔹 Beyond Basic Chatbots: I engineer autonomous AI Agents (LangGraph, LangChain, CrewAI, MCP) that execute complex, multi-step business logic and real-world tasks. 🔹 Data-Driven AI (RAG): I build robust Retrieval-Augmented Generation pipelines using Vector Databases (Pinecone, Supabase) so your AI answers reliably using your private data—with zero hallucinations. 🔹 Production-Ready Architecture: AI is useless if the core app crashes. I ensure seamless integration into robust Node.js and Next.js architectures with enterprise-grade security and multitenant authentication (Keycloak/SSO). 🔹 Human-in-the-Loop Safety: I implement strict guardrails and prompt security to keep your proprietary data protected and your operations reliable. CORE TECH STACK & EXPERTISE: 🧠 AI & LLMs: LangGraph, CrewAI, Custom Agent Workflows, Prompt Engineering, RAG Pipelines. 💻 Frontend: React.js, Next.js, TypeScript, UI/UX optimization. ⚙️ Backend & Databases: Node.js, Nest.js, GraphQL, PostgreSQL, MongoDB, Vector Databases. ☁️ Cloud & DevOps: Docker, Microservices, Stripe API, Keycloak, REST APIs. TYPICAL ENGAGEMENTS: ✔️ Custom AI Agents: Building multi-agent systems for lead generation, data extraction, or automated customer support. ✔️ Internal AI Knowledge Bases: Designing RAG systems to instantly query massive amounts of internal PDFs, contracts, or company data. ✔️ Legacy Modernization: Retrofitting your existing web applications with modern, AI-native capabilities. ✔️ Full-Stack Development: End-to-end development of scalable SaaS platforms from architecture to deployment. My goal is to deliver measurable ROI, not just lines of code. If you want a technical partner who communicates transparently and delivers on time, let’s talk. Send me a message to discuss your current bottlenecks, and let's map out an automation strategy that scales. --- 🚀 EXPLORE MY WORK Please view the Portfolio section below to see live interactive demos of my AI-native applications and my complete 6-year engineering showcase. For source code and open-source contributions, you can search my developer handle on GitHub: Talhii

Research Publications | AI Development | Data Analysis I'm a Data Scientist with 2+ years of experience in Data Scraping, Data Analysis, Data Visualization, Machine Learning, Deep Learning, Computer Vision, and NLP. I work primarily in Python and R/RStudio. What I Do: 📊 Statistical Analysis, Time Series Analysis, Quantitative & Predictive Analysis 🤖 Designing, developing, and fine-tuning ML/DL models that deliver real impact 🚀 Building models from scratch or optimizing existing ones Background: Currently pursuing a Master's in Data Science with hands-on experience across Machine Learning, Deep Learning, and Advanced Analytics. Technical Skills: Languages: Python 🐍, R 📈 Frameworks: TensorFlow, Keras, PyTorch, Scikit-learn, Hugging Face Transformers, XGBoost, LightGBM, CatBoost, OpenCV, FastAPI, Flask, Streamlit Libraries: NumPy, Pandas, Matplotlib, Seaborn, Plotly, Statsmodels, SciPy Data Tools: Selenium, Scrapy, SQL, Power BI, Tableau, AWS (S3, Glue, Redshift), GCP, Azure ML Others: MATLAB, Git, Docker, Google Earth Engine Project Experience: I've delivered projects across healthcare, finance, computer vision, and geospatial analytics. Some highlights: Built deep learning models for drought prediction using 20 years of satellite data Developed medical image classification systems for cervical cancer detection using DenseNet, ResNet, and EfficientNet architectures Designed sales forecasting pipelines and stock market analysis dashboards with interactive visualizations Created an AI voice assistant for paramedics Built a real-time multi-camera object tracking system Developed a student pressure dashboard powered by D3.js Explored XAI methods (GradCam, SHAP, LIME) for model interpretability Implemented models for churn prediction and match outcome forecasting These projects combine machine learning, deep learning, and data science to deliver practical, impactful solutions. What I Offer: ✅ Machine Learning Models: Build, fine-tune & deploy high-performance ML solutions ✅ Deep Learning Architectures: Custom DL models tailored to your needs ✅ Python Programming: Clean, optimized code for ML & data science tasks ✅ Data Analytics & Visualization: Insightful analysis and compelling visuals ✅ Data Scraping & Parsing: Data extraction using BeautifulSoup, Scrapy, and Selenium Why Work With Me: ✨ Strong expertise in both ML and DL ✨ Clear communication throughout projects ✨ Fast delivery with professional support ✨ Focus on quality and client satisfaction I take pride in delivering solutions that work. My approach is straightforward: build powerful models, provide actionable insights, and ensure clients are happy with the results. Let's Work Together: If you need someone who can take your machine learning projects to the next level, I'm here to help turn your ideas into reality. 🚀

I build production Algo-trading systems, from market data ingestion to live execution; for funds, prop desks, and serious retail traders. 9+ years in software engineering, the last several spent almost exclusively on trading infrastructure: IBKR/MT5/FIX execution, tick-level data pipelines, and causal ML for signal generation. I run my own live trading platform, so I'm not learning on your dime — I ship what I already operate. What I Build: ⤷ End-to-end algo trading systems (data → signal → execution → risk) ⤷ Broker/exchange integrations: IBKR API, MT4/MT5 (MQL5 EAs), Binance, Bybit, Polymarket ⤷ Low-latency execution infrastructure (Dockerized IB Gateway, multi-instance live trading, C# ↔ MQL5 bridges) ⤷ Causal inference for markets: PCMCI+, VarLiNGAM, DYNOTEARS, Granger/Transfer Entropy — used to filter spurious signals before they hit a backtest ⤷ ML signal models: LightGBM, XGBoost, LSTM/TCN, meta-labeling over causal-discovery gates ⤷ Backtesting & research stacks: NautilusTrader, Backtrader, Zipline, QuantConnect, Qlib ⤷ Market microstructure work: LOB/MBP-10 data, Hawkes processes, Hayashi-Yoshida covariance, price discovery (Hasbrouck/Gonzalo-Granger) ⤷ Options pricing & Greeks (Black-76, BSM, second-order Greeks) for hedging and 0DTE workflows ⤷ Financial data engineering: Databento, TimescaleDB, Parquet/Arrow pipelines Core Stack: ✓ Backend: Python (FastAPI, Django), C#/.NET, Rust, C++ ✓ Data: TimescaleDB, PostgreSQL, Redis/Valkey, Parquet, Apache Arrow/PyArrow ✓ Cloud/Infra: AWS (ECS, Lambda, RDS), Docker, Terraform, Packer, GitHub Actions CI/CD ✓ Trading: IBKR API, MetaTrader 5/MQL5, TradingView, Databento (GLBX.MDP3/MBP-10) ✓ ML/Causal: PCMCI+, CMIknn, LightGBM, XGBoost, scikit-learn, statsmodels Why Clients Choose Me: ✓ I operate a live trading platform myself — I understand uptime, restart cycles, and the failure modes that only show up in production ✓ Rigorous methodology: I don't just backtest, I stress-test causal assumptions before trusting a signal ✓ Clean, documented handover — you're not locked into me ✓ Clear async communication with regular progress updates Recent Results: - Rebuilt an IBKR Gateway deployment to eliminate recurring 12-hour restart cycles caused by GDI handle leaks - Designed a causal-discovery pipeline (PCMCI+/CMIknn) identifying dominant cross-asset drivers in equity stress regimes - Architected a C# Worker Service + MQL5 EA bridge for automated MT5 execution - Live trading volume: $80M+ across managed strategies (2025) - Built AWS Savings Plan / Reserved Instance cost model cutting infra spend without sacrificing uptime SLAs Send me your requirements and I'll respond within 2-6 hours with a concrete plan — not a template pitch.

I help businesses eliminate repetitive work, connect disconnected systems, and scale operations through AI-powered automation, machine learning, computer vision, and production-ready backend systems. Who I am I am an AI/ML Engineer and Automation Specialist with expertise in machine learning, large language models (LLMs), AI agents, computer vision, workflow automation, and Python development. II build reliable AI systems that solve measurable business problems. What I Do 1. AI/ML Engineering – Predictive analytics, classification, recommendation systems, anomaly detection, custom ML pipelines, and fine-tuning LLMs such as Llama, Mistral, and OpenAI models on proprietary data. 2. LLM Integration & Agentic AI – LLM powered applications, autonomous AI agents, RAG (retrieval-augmented generation), long-term context, function calling, tool use, and workflow orchestration with OpenAI GPT-4o, Claude, Gemini, Llama, and Mistral. 3. Computer Vision & Edge AI – Real-time object detection, tracking, counting, face recognition, license plate recognition, OCR, ROI/zone logic, and anomaly detection using YOLOv8/v9/x, OpenCV, DeepStream, TensorRT, FAISS, CNNs, and NVIDIA GPUs. I build local and cloud-connected RTSP camera pipelines with alerts, analytics, and structured API outputs. 4. Voice AI & Conversational Systems – Inbound/outbound voice agents using VAPI, Retell AI, and Twilio; AI chatbots for websites, WhatsApp, Slack, and SMS; and omnichannel assistants with shared context. 5. Workflow Automation – n8n, Make, Zapier, and Python automations connecting CRMs, databases, email, Slack, APIs, and business tools. AI workflows include classification, extraction, lead qualification, content generation, alerts, and follow-up actions. 6. Python Development & Backend Systems – RESTful APIs, ETL/data pipelines, web scraping, event-driven services, custom scripts, and AI backends using FastAPI, Django, Flask, Node.js, PostgreSQL, MySQL, MongoDB, and Redis. Real Systems I Have Built • Agentic AI Camera Platform – A multi-tenant computer vision system processing live RTSP streams on NVIDIA GPUs. When anomalies such as smoke, fire, falls, accidents, or security events are detected, the agentic workflow gathers context, stores incidents in dedicated tables, triggers alerts, generates summaries, calls APIs, and performs configured workflow tasks. • Parking & Traffic Intelligence – Vehicle classification, tracking, and counting for multi-storey buildings and mall parking. The system distinguishes cars and motorcycles, detects entry/exit direction, wrong-way movement, possible collisions, and parking-space availability. • Claude Video Production Automation – Built a reusable Claude Code, Skills, Cowork, and AI agent pipeline converting PPTX and YouTube research into scripts, image/video prompts, voiceovers, timed scenes, Shorts, and CapCut-ready videos. • So Special Mobile Mechanic – AI powered mobile and operations platform with dispatch, customer tracking, automated notifications, and backend dashboards. • AL Arabi Company – Dispatch system for operations and maintenance with real-time job assignment, status tracking, and reporting. • Mystical Agency & Intero Digital – AI automation and proposal-generation systems that reduced proposal creation time from two days to under two hours. • Clinic WhatsApp Automation – AI chatbot for appointment booking, prescription reminders, FAQs, and patient follow-ups integrated with scheduling. • E-commerce Recommendation Engine – Custom ML model using browsing and purchase history. Technology Stack Languages: Python, JavaScript/Node.js, SQL ML/AI: TensorFlow, PyTorch ecosystem tools, scikit-learn, Hugging Face, LangChain, LlamaIndex, YOLOv8/v9/x, OpenCV, DeepStream, TensorRT, Faiss, CNNs LLMs: OpenAI GPT-4o, Claude, Gemini, Llama, Mistral LLM Quality: response evaluation, prompt analysis, output validation, edge-case testing, task decomposition AI Video Automation: Claude Code, Claude Skills, Claude Cowork, AI agents, PPTX-to-video, Canva, CapCut, Gemini Flow, Veo 3 Automation: n8n, Make, Zapier Voice AI: VAPI, Retell AI, Twilio Vector Databases: Pinecone, Weaviate, Chroma, FAISS Backend/Data: FastAPI, Django, Flask, REST APIs, PostgreSQL, MySQL, MongoDB, Redis, Pandas, NumPy, SQLAlchemy Cloud/DevOps: AWS SageMaker, Lambda, EC2, ECS, S3, GCP Vertex AI, Azure, Docker, Docker Compose, GitHub Actions, Linux How I Work I begin with discovery to define goals, inputs, risks, and success criteria. I then design, build, test, and refine the solution with your team before deployment, handover, and documentation. Ideal Clients You are a strong fit if you need AI/ML models, computer vision, AI voice agents, LLM chatbots, autonomous AI agents, RAG, workflow automation, API integrations, custom backends, or production-ready systems that replace manual work. Let’s Talk Send me a message or invite me