I’m an Analytics Engineer and Cloud Data professional with 17+ years of experience across healthcare analytics, data engineering, cloud integration, BI, governance, and secure data platforms. My work spans Azure, Microsoft Fabric, ADF, Synapse, Databricks, Snowflake, SQL, Python, HL7, FHIR, IoMT pipelines, HIPAA-aware data systems, and AI-ready analytics workflows. I specialize in building the analytics layer between raw data and business decisions: clean data models, trusted KPIs, governed datasets, secure pipelines, and dashboards that leadership teams can actually rely on. 𝐖𝐡𝐚𝐭 𝐈 𝐜𝐚𝐧 𝐡𝐞𝐥𝐩 𝐰𝐢𝐭𝐡 ✅ 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 & 𝐁𝐈 Clinical, operational, IoMT, device telemetry, EHR, HL7, FHIR, HIPAA-aware dashboards, executive reporting, and healthcare data quality. ✅ 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 SaaS metrics, eCommerce analytics, customer analytics, marketing analytics, revenue reporting, KPI frameworks, semantic models, and BI-ready datasets. ✅ 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Azure Data Factory, Microsoft Fabric, Synapse, Databricks, Snowflake, SQL, Python, API integrations, data ingestion, ETL/ELT pipelines, and cloud data modernization. ✅ 𝐀𝐈-𝐑𝐞𝐚𝐝𝐲 𝐃𝐚𝐭𝐚 & 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 AI-ready datasets, anomaly detection support, ML-ready pipelines, automated reporting workflows, intelligent insights, and structured data foundations for AI use cases. ✅ 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 & 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 HIPAA, HITRUST, NIST, RBAC, data lineage, metadata, auditability, data validation, access controls, and secure-by-design analytics architecture. 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐢𝐧𝐜𝐥𝐮𝐝𝐞𝐬 👉 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐦𝐨𝐝𝐞𝐫𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 Designed secure Azure-based pipelines for clinical, operational, IoMT, and medical device data using ADF, Synapse, ADLS, Databricks, API integrations, HL7, and FHIR standards. 👉 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐁𝐈 𝐚𝐧𝐝 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 Delivered dashboards combining operational, clinical, device, and risk indicators to help leadership teams monitor performance, reliability, and compliance. 👉 𝐂𝐥𝐨𝐮𝐝 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Built governed data layers, SQL models, data mappings, validation workflows, and reporting-ready datasets across Azure, Fabric, Synapse, Databricks, Snowflake, and SQL-based environments. 👉 𝐀𝐈-𝐫𝐞𝐚𝐝𝐲 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬 Prepared structured and reliable datasets for anomaly detection, predictive analytics, device monitoring, and advanced healthcare insights. 👉 𝐒𝐞𝐜𝐮𝐫𝐞 𝐝𝐚𝐭𝐚 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Implemented data quality, lineage, metadata, retention, identity controls, and compliance-aligned processes for sensitive healthcare and enterprise datasets. 𝐌𝐲 𝐠𝐨 𝐭𝐨 𝐓𝐨𝐨𝐥𝐬 𝐚𝐧𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 Azure Data Factory, Microsoft Fabric, Azure Synapse, Azure SQL, ADLS Gen2, Databricks, Snowflake, SQL, Python, PySpark, dbt, Power BI, Tableau, HL7, FHIR, EPIC, IoMT, APIs, Event Hub, Azure IoT Hub, Delta Lake, RBAC, IAM, HIPAA, HITRUST, NIST, and data governance frameworks. If your team needs cleaner healthcare analytics, better BI models, secure cloud data pipelines, or AI-ready datasets, send me a message and I’ll help map the right analytics architecture for your business.

I am building AI products, Agentic AI systems, and scalable SaaS applications from idea to production. Hi, I'm Abubakar Majid, an 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐚𝐧𝐝 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 with 3+ years of experience delivering AI-powered products, automation systems, and modern web applications for startups, founders, and businesses worldwide. I specialize in combining Generative AI, Agentic AI, LLMs, and modern full-stack technologies to create intelligent software that automates workflows, improves productivity, and scales efficiently. I work across the entire product lifecycle, including architecture, frontend development, backend APIs, AI integrations, cloud deployment, and production optimization. 𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝 ✅ AI SaaS Platforms ✅ AI Agents and Multi-Agent Systems ✅ Custom GPT Applications ✅ AI Chatbots with Memory and RAG ✅ Workflow Automation Systems ✅ AI Content Generation Platforms ✅ Document Processing and Knowledge Systems ✅ Internal Business Tools ✅ Startup MVPs and Production SaaS Products ✅ SEO-Optimized Web Applications 𝐂𝐨𝐫𝐞 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 Agentic AI Development Design and build autonomous AI agents capable of planning, reasoning, tool usage, and multi-step execution using modern agent frameworks. 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: LangGraph, LangChain, CrewAI, OpenAI Agents SDK, OpenAI Responses API, MCP Servers, Multi-Agent Architectures Generative AI and LLM Applications Develop production-ready AI products powered by large language models and advanced prompting strategies. 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: RAG Systems, Structured Outputs, Function Calling, Tool Use, Memory Systems, Context Management, Document Understanding, AI Assistants AI Automation and Workflow Systems Build intelligent automations that reduce manual work and improve business operations. 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: n8n, Make, Zapier, API Integrations, CRM Automation, Lead Processing, Document Automation, Email Workflows Full-Stack Development Develop fast, scalable, and maintainable web applications with modern frontend and backend technologies. 𝐅𝐫𝐨𝐧𝐭𝐞𝐧𝐝: Next.js, React, TypeScript, Tailwind CSS, Zustand, React Query, Server Components, SSR, SEO Optimization Backend: FastAPI, Node.js, Express.js, PostgreSQL, Supabase, MongoDB, Authentication Systems, REST APIs 𝐀𝐈 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 Deploy AI systems and scalable applications to production environments with monitoring and optimization. Technologies: Docker, Vercel, AWS, DigitalOcean, CI/CD, Reverse Proxies, Background Jobs, Queue Systems, Logging, Monitoring 𝐒𝐨𝐦𝐞 𝐨𝐟 𝐦𝐲 𝐰𝐨𝐫𝐤 AI Writing Platform Built an AI-powered writing platform featuring AI agents, content generation pipelines, scalable APIs, and SEO-focused frontend architecture. Stack: OpenAI, LangGraph, FastAPI, Supabase, Next.js, Docker AI Detection SaaS Platform Developed a complete AI SaaS application including frontend, backend, authentication, payment integration, and deployment infrastructure. Stack: GPT Models, FastAPI, Supabase, Next.js, PostgreSQL, Vercel AI Review Analytics System Created NLP pipelines for sentiment analysis, topic clustering, review classification, and business intelligence reporting. Stack: Python, Pandas, spaCy, Machine Learning Actor Portfolio Platform Built responsive, high-performance user interfaces optimized for SEO, accessibility, and user experience. Stack: Next.js, TypeScript, Tailwind CSS 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐞𝐬 𝐈 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 SaaS Startups AI Startups E-commerce Businesses Marketing Agencies Content Platforms Education Technology Productivity Software Internal Enterprise Tools Technologies AI and Machine Learning OpenAI, GPT Models, LangChain, LangGraph, CrewAI, Hugging Face, Transformers, PyTorch, TensorFlow, Scikit-learn, RAG, Vector Databases, Embeddings Databases and Search PostgreSQL, Supabase, MongoDB, Pinecone, FAISS, Vector Search Backend FastAPI, Node.js, Express.js, REST APIs, Authentication, Webhooks, Payment Integrations Frontend React, Next.js, TypeScript, Tailwind CSS, Responsive Design, SEO Optimization DevOps and Cloud Docker, AWS, DigitalOcean, Vercel, CI/CD, Linux Servers, Monitoring 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐌𝐞 ✔ End-to-end ownership from idea to deployment ✔ Strong AI and full-stack engineering expertise ✔ Scalable and maintainable architecture decisions ✔ Clear communication and reliable delivery ✔ Startup-friendly and business-focused approach ✔ Long-term support for growth and scaling Whether you need an AI SaaS MVP, AI agents, automation systems, LLM applications, or a complete full-stack product,𝐈 𝐜𝐚𝐧 𝐡𝐞𝐥𝐩 𝐭𝐮𝐫𝐧 𝐲𝐨𝐮𝐫 𝐢𝐝𝐞𝐚 𝐢𝐧𝐭𝐨 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧. 𝐋𝐞𝐭'𝐬 𝐛𝐮𝐢𝐥𝐝 𝐬𝐨𝐦𝐞𝐭𝐡𝐢𝐧𝐠 𝐯𝐚𝐥𝐮𝐚𝐛𝐥𝐞 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫.

I help businesses, hospitals, startups, and research teams convert messy operational data into intelligent decision-support systems using Machine Learning, Mathematical Optimization, and Predictive Analytics. My core work includes forecasting, scheduling, resource allocation, clinical/engineering data analysis, AI model development, and optimization dashboards that help clients reduce delays, improve utilization, and make faster data-driven decisions. I specialize in Python-based analytical systems, that do not only analyze data but also support real operational decisions. I combine Operations Research, Machine Learning, Forecasting, Simulation, and Python-based analytics to solve problems related to scheduling, resource allocation, prediction, classification, capacity planning, business intelligence, and system optimization. What I Can Help You With Computational Optimization & Mathematical Modeling I formulate and solve real-world decision problems using linear programming, mixed-integer linear programming, scheduling models, resource allocation models, routing models, and constraint-based optimization. I work with Python, Pyomo, CPLEX logic, CBC solver, MATLAB, GAMS, and Excel-based optimization tools. Healthcare Optimization & Decision Support I have strong experience in healthcare operations research, including operating room scheduling, patient-flow optimization, hospital resource planning, PACU/ICU capacity analysis, staff allocation, and AI-driven healthcare decision-support frameworks. My focus is on improving utilization, reducing delays, and supporting evidence-based operational decisions. Machine Learning & Predictive Analytics I develop supervised machine learning models for regression, classification, forecasting, risk prediction, and performance analysis. My experience includes Random Forest, XGBoost, CatBoost, SVM, Decision Trees, feature engineering, model validation, and performance evaluation using MAE, RMSE, R², accuracy, AUC, F1-score, and other KPIs. Computer Vision & Image-Based AI I work on image preprocessing, feature extraction, computer vision regression/classification, medical image analytics, segmentation-based analysis, and AI-assisted visual decision systems. I can support projects involving OpenCV, Python, image datasets, clinical imaging features, and machine learning-based image interpretation. Forecasting & Business Analytics I help businesses and researchers build forecasting models, demand prediction systems, KPI dashboards, market analytics, operational performance reports, and decision-ready business insights. I can analyze structured data and translate results into clear recommendations for management, research, or client-facing reports. Research, Reports & Technical Documentation Along with modeling and analytics, I prepare professional technical reports, research manuscripts, white papers, methodology sections, literature reviews, results interpretation, and publication-style documentation. I can turn raw datasets, models, and technical concepts into clear, polished, and client-ready deliverables. Tools & Technologies Python | Pyomo | Scikit-learn | Pandas | NumPy | Matplotlib | OpenCV | MATLAB | Simulink | CPLEX | CBC Solver | GAMS | Excel Solver | Machine Learning | Optimization | Forecasting | Predictive Modeling | Computer Vision | Business Analytics | Decision Support Systems Industries I Work With Healthcare Systems Business Operations Supply Chain and Logistics Manufacturing and Production Systems Research and Academic Projects AI/ML-Based Decision Systems Engineering and Technical Consulting My goal is simple: to help you solve complex problems with clear models, reliable data analysis, and practical decision-support outputs. Whether you need an optimization model, a machine learning pipeline, a forecasting system, a computer vision workflow, or a complete analytical report, I can help you build a solution that is technically sound, well-documented, and ready for real-world use. Let’s connect and turn your operational chaos into confident, data-driven decisions using the power of analytics, optimization, and intelligent AI systems.

4 years of experience as a freelance statistician & econometrician & 10 years of teaching with a strong background in data analysis, visualization, and interpretation. - MPhil in Statistics & Research from IQRA university in Pakistan - Freelance statistician helping clients extract insights using SPSS, R, Stata, Excel, and a strong foundation in Python and Amos. - Have massive experience in handling data pulling, manipulating, processing, building models, and survey data, time series and panel data modelling -Let's bring something fruitful from your data and get rid of the headache of data.

Ambitious Computer Engineer, experienced and interested in Data Science and Machine Learning Domains and highly skilled in Python. ✨ Languages experienced in: - Python - Java - C ✨Packages experienced in: - NumPy - Matplotlib - scikit-learn - Pandas - PyTorch ✨What I can offer: Data Science: - Data Wrangling - Data Cleaning - Data Visualization - Data Modeling Machine Learning: - Decision Tree - Linear Regression - Logistic Regression - Random Forest - KNN - K-means - CNN - ANN

I'm a lead Machine Learning Engineer with 8+ years of experience delivering AI/ML solutions from concept to large-scale, secure and scalable deployment. Experienced in full project lifecycle management and expert in Terraform, Docker, Jenkins and Kubernetes with a strong track record in building automated CI/CD pipelines, containerized microservices and cloud-native ML systems. Kaggle Grandmaster, published researcher and trusted expert in GenAI and LLMs. Technical Skills - Programming languages: Python, SQL, Shell Scripting, Java (intermediate), JavaScript (intermediate in Node.js, Next.js) - Frameworks and Libraries: PyTorch, TensorFlow, Transformers, LangChain, NLTK, OpenCV - GenAI and LLM Tools: Prompt Engineering, RAG, GGUF, MCP, Agentic AI, Quantization and Fine-tuning - DevOps and Cloud: Git, Docker, Jenkins, Kubernetes, Terraform, AWS, Azure, GCP, Kafka, Grafana, RESTful APIs, AWS CDK I bring solid, proven expertise backed by real world outcomes. I specialize in designing scalable, production ready pipelines using LLMs, RAG, semantic search, MCP servers, Multi-Agent system and cloud-based DevOps systems. I have delivered solutions that directly impacted business growth, performance and efficiency. What I bring to the table: - Real experience building production level AI systems , not just prototypes - Focus on business value, efficiency, scalability and impact - A grounded, no-fluff approach with clean code and solid delivery - Leadership of cross functional ML teams, client success stories and long term results Why Choose Me? - Passionate and always try robust stratgies - Hands on deployment experiance of AI pipelines - Proven business impact (revenue, performance, scalability) - Communication & team collaboration - Post project support and clean, documented code - Your data, models and ideas are treated with strict confidentiality

I am a passionate and attentive data scientist with with several years of experience and a Master's Degree who would love to help you with all your data needs. Here are some of the services I provide: -Web scraping -Data Analysis -Machine Learning -Google Data Studio and Google Analytics -and more! If I can help you in any way, don't hesitate to reach out. I look forward to helping you.

If the problem involves AI touching real decisions—and getting it right matters—I’m usually a good fit. I routinely deliver what would take most teams a week in a single day. As one former Upwork client put it: “Got a week’s worth of work done in less than an hour due to Jonathan’s expertise. Would work with him again, no question.” That speed comes from deep domain expertise and fluency with modern AI tooling, which I use as a force multiplier—not a shortcut. I move quickly because I know exactly what to build, what not to build, and how to avoid rework through systematic testing. Most of my work sits in environments where systems influence money, risk, or operations, and where errors are expensive. The goal is not experimentation or novelty. It is building systems that work the first time, explain their decisions, and remain reliable under scrutiny. I led the design and implementation of an AI-driven small-business credit platform for a publicly traded lender (~$40M+ annual revenue). The system automated the majority of application decisions by combining structured financial data, document understanding, and retrieval-augmented analysis with tool-enabled research. Within a controlled environment, the system could query internal data, perform constrained external searches, and assemble a 30-point underwriting profile aligned with senior credit-analyst reasoning. Crucially, the system enforced confidence thresholds and escalation logic. Only the most complex 10–15% of applications were routed to expert underwriters, allowing human effort to concentrate where judgment actually added value. Manual review fell sharply without increasing risk. Security was treated as a first-order constraint. All PII was isolated within private network boundaries, with encrypted storage and tightly scoped access. Even large-language-model interactions—including external research—were routed through secured infrastructure so sensitive data never left controlled environments. Most engagements begin with a short diagnostic phase. I’m direct about whether I’m needed at all—and when I’m not, I say so. Clients often use a less expensive developer for execution once the critical architectural and risk decisions are made. That discipline is part of the job. Selected Systems I’ve Built At Finally, a $100M Series-B payroll company, I designed and shipped a production payroll platform in roughly six weeks, making early architectural decisions that prevented later rewrites and operational debt. In academic publishing, I helped build and stabilize Refine.ink, an AI-driven peer-review platform used by faculty at leading U.S. universities, where rigor, explainability, and predictable behavior were non-negotiable. As Refine.ink’s co-founder put it: “Jonathan combines deep technical ability with unusually strong judgment. He consistently identified the right problems to solve and built systems we could trust in production.” — Ben Golub, Co-Founder, Refine.ink; former Professor of Economics and Computer Science at Harvard; current Professor of Economics at Northwestern University I’ve also built agentic and multimodal systems that execute real workflows: voice-driven legal intake systems that conduct structured interviews and route qualified matters directly into case management; and computer-vision pipelines where I fine-tuned custom object-detection models to classify industrial weld defects—often only a few pixels wide—achieving ~95% accuracy with a lightweight human-review loop. I’m typically brought in when teams need rapid progress without mistakes—when systems have to move fast and still hold up in production. I work quickly because I’m an expert at what I do and deeply fluent in AI tooling, which allows me to compress timelines without cutting corners.

Hi — I’m Farshad, a quantitative developer and AI engineer with a PhD in Artificial Intelligence and 10+ years of experience in algorithmic trading, AI/ML, and Python-based trading infrastructure. I build production-grade algorithmic trading systems across equities, options, crypto, and prediction markets (IB/Thinkorswim,tradestation,polymarket), covering the full lifecycle from research and backtesting to live execution and risk management. **Live trading & production experience** * ~$2.5M capital under management (2026) * 2+ years of continuous live deployment * Thousands of real-time trades executed across equities, options, and crypto * Only $8M live trading volume in Q1–Q2 2024 * 14,000+ backtests run in 2024-2025 * 100,000+ lines of production trading code written in 2024 **What I specialize in** * Algorithmic trading strategy development * Options strategies (debit/credit spreads, short premium, Greeks analysis) * Volatility and regime forecasting using AI/ML * Agentic trading workflows (autonomous model + execution + risk loops) * Backtesting and execution infrastructure * Market microstructure and anomaly detection **Platforms & infrastructure** * QuantConnect Lean (Python) * NautilusTrader * Interactive Brokers, Binance * Polygon market data * PostgreSQL / cloud databases * Docker & cloud-based deployments **Open-source contribution** * Active contributor to an open-source options trading framework for QuantConnect: (focused on production-ready options strategy architecture and execution logic) I work as a hands-on engineer who can take trading ideas from prototype to production, with transparent communication and structured delivery.

🚀Hi! I help startups go from demo → market-ready AI product - fast! I plug into your team and ship production ready features that customers love. 🏆 Top 1% (Expert-vetted) | 8+ years| 100% JSS | 35+ Delighted Clients | 18+ E2E Deployments 🎯 "𝘒𝘶𝘯𝘫𝘢𝘯 𝘪𝘴 𝘢𝘯 𝘢𝘣𝘴𝘰𝘭𝘶𝘵𝘦 𝘨𝘦𝘮! 𝘚𝘩𝘦 𝘸𝘦𝘯𝘵 𝘢𝘣𝘰𝘷𝘦 𝘢𝘯𝘥 𝘣𝘦𝘺𝘰𝘯𝘥. 𝘛𝘦𝘢𝘮𝘪𝘯𝘨 𝘶𝘱 𝘸𝘪𝘵𝘩 𝘩𝘦𝘳, 𝘸𝘦 𝘣𝘶𝘪𝘭𝘵 𝘳𝘰𝘣𝘶𝘴𝘵 𝘥𝘢𝘵𝘢 𝘱𝘪𝘱𝘦𝘭𝘪𝘯𝘦𝘴, 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘦𝘥 𝘓𝘓𝘔𝘖𝘱𝘴, 𝘵𝘳𝘢𝘯𝘴𝘪𝘵𝘪𝘰𝘯𝘦𝘥 𝘧𝘳𝘰𝘮 𝘧𝘢𝘯𝘤𝘺 𝘥𝘦𝘮𝘰𝘴 𝘵𝘰 𝘢 𝘴𝘤𝘢𝘭𝘢𝘣𝘭𝘦 𝘈𝘐 𝘱𝘳𝘰𝘥𝘶𝘤𝘵 𝘵𝘩𝘢𝘵 1000𝘴 𝘰𝘧 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘭𝘰𝘷𝘦!" - CTO, Healthcare startup, SF (1 of many 5-star reviews) Over 7+ years on Upwork, I've helped startups and enterprises across sectors - Marketing, Healthcare, Law, Education, and Agribusiness - translate AI into measurable business ROI by building the right data and ML foundations. Whether collaborating with 1000+ employee companies or lean 2-person startups, I adapt to the team’s needs: reporting directly to CEOs or CTOs as an AI/Data Lead, or integrating as a hands-on contributor alongside in-house developers. I bring a “brain-for-hire” + hands-on mindset - tackling strategic and technical challenges with equal enthusiasm, always focused on delivering outcomes, not overhead. 👀 See 8+ Case Studies & Demos: totemxlabs dot com/#casestudies 🎯 Recent Success Stories (2024-2025) 1. Graph RAG for Marketing & Strategic decisions Implemented knowledge graph-powered RAG systems using Neo4j for marketing intelligence and SEO optimization - enabling sophisticated knowledge checks and relationship-based insights that traditional RAG cannot achieve. 2. Workplace Safety Vision System Deployed end-to-end computer vision solution for workplace health and safety compliance - real-time hazard detection, PPE verification, and automated incident reporting. 3. Healthcare Diagnostic Knowledge Graph Developed evidence-based diagnostic system using knowledge graphs for healthcare - producing auditable, traceable diagnostic reasoning paths that meet clinical documentation standards. 🧭 My Proven AI Product Process: Discovery: Identify high-ROI AI opportunities aligned with your goals. Data Assessment: Evaluate data availability, relevance, quality. Solution Design: Define user journeys, tech stacks, evaluation frameworks. Development: Optimized sprints for cost-effective, robust AI solutions (min. tech debt). Deployment: Scalable architectures, rigorous testing for production readiness. 💡 Technical Expertise: GenAI & LLMs: LLM Ops (Fine-tuning, Prompt Engineering, RAG, Agentic Workflow, Multi-agent systems, Memory Management), LangChain, LangGraph, LlamaIndex, LangServe; Vector Search (Pinecone, Weaviate, Chroma, FAISS). AI/ML & MLOps: Predictive Analytics, Recommender Systems, RLHF; Model Lifecycle, MLflow, Feature Stores; PyTorch, TensorFlow, Scikit-learn. Cloud & Infra (Multi-cloud): AWS (Lambda, ECS, ElastiCache, DynamoDB, API Gateway), Azure, GCP, Vertex AI, SageMaker; Docker, Kubernetes (EKS/GKE). Software & Data Eng: Python (expert), Fullstack; FastAPI, Flask, Django; REST, GraphQL, OpenAPI, AsyncIO; Batch/Stream (Airflow, Spark, Kafka), Pandas, Polars, dbt; ETL/ELT. DBs/Arch/DevOps: PostgreSQL, MySQL, DynamoDB, MongoDB, Vector DBs (Pinecone, Weaviate, ChromaDB), Neo4j; Microservices, GitHub Actions, Terraform, CI/CD pipelines. 🤝 Why Partner With Me? I help architect and develop E2E AI solutions merging tech excellence with business acumen. Let's transform the AI wave into your competitive edge. ✅DM me if you have an exciting problem to solve! —Updated January, 2026— Latest LLMs (2025-26): GPT-5.2 (OpenAI's flagship with 26% lower hallucination rate) Claude 4.5 Opus & Sonnet 4.5 (200K context, breakthrough coding performance) Gemini 3 Pro & Flash (Deep Think mode, multimodal excellence, 1M token context) DeepSeek V3.2 & R1 series (685B parameters, hybrid thinking/non-thinking modes) Qwen 3 series (open weight dense and mixture-of-experts (MoE) model for reasoning tasks) Agentic AI Frameworks: Langchain & LangGraph (stateful graph-based workflows, production-grade orchestration) OpenAI Agents SDK (lightweight with guardrails and handoffs) CrewAI (role-based multi-agent collaboration, human-in-the-loop) LlamaIndex Agents (RAG-first agent capabilities) AI workflow automation: n8n Knowledge Graphs & Graph RAG: Neo4j 2025 features: Community summaries, parallel retrievers, LLM Knowledge Graph Builder Neo4j Aura Graph Analytics Graph RAG architecture Cypher query optimization, graph embeddings for ML Agentic knowledge graph construction with provenance Computer Vision Applications: Workplace safety, Video generation Multimodal Vision Language Models (VLMs) Context engineering for high quality content generation