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Top Rated AI Agent Engineer | RAG | Multi-Agent Systems | OpenAI & Claude | Automation Expert Are you looking to build AI that actually delivers business results—not just another chatbot demo? I help startups, SaaS companies, and enterprises build production-ready AI systems that automate workflows, improve decision-making, reduce operational costs, and scale reliably. 🔹 Built 100+ AI-powered solutions 🔹 Top Rated AI/ML Engineer 🔹 Specialized in AI Agents, RAG, and Business Automation 🔹 Focused on real-world deployment, scalability, and measurable ROI ## What I Can Help You Build ✅ AI Agents & Multi-Agent Systems * Autonomous AI workflows * Research and analysis agents * Customer support agents * Sales and lead-generation agents * Multi-agent orchestration using LangGraph ✅ RAG (Retrieval-Augmented Generation) * Knowledge base chatbots * Internal document assistants * Citation-based AI systems * Enterprise search solutions * Vector databases (Pinecone, FAISS, Chroma) ✅ Generative AI & LLM Applications * OpenAI GPT-4o * Claude API * Gemini * Custom AI assistants * AI-powered SaaS features ✅ Workflow Automation * n8n automation * Zapier automation * AI-driven business processes * CRM integrations * API integrations ✅ Backend & AI Infrastructure * Python * FastAPI * LangChain * LangGraph * Vector Databases * Cloud Deployment * Production AI Architecture ## Recent Results ✔ Built AI customer support agent that reduced support workload by 60% ✔ Developed enterprise RAG platform achieving 95%+ response accuracy ✔ Automated business workflows saving 100+ hours per month ✔ Built multi-agent systems for research, reporting, and operational automation ## Why Clients Hire Me Many developers can build an AI demo. I build systems that: ✅ Work reliably in production ✅ Scale as your business grows ✅ Integrate with your existing tools ✅ Deliver measurable business value ✅ Are maintainable and cost-efficient ## Industries I Work With ✔ SaaS Startups ✔ AI Product Companies ✔ E-commerce Businesses ✔ Consulting Firms ✔ Enterprise Teams ✔ Operations & Support Teams Let's Build Something That Creates Real Business Impact Whether you're building an AI product, implementing RAG, developing AI agents, or automating business processes, I can help you design and deploy a solution that works in production. Send me a message with your project idea, and I'll suggest the best approach to get started.

AI / ML / Agentic AI LLM / Langchain / RAG ChatBots AI / Machine Learning & Computer Vision specialist with hands-on experience building, training, and deploying deep learning models for real-world applications. I specialize in YOLO-based object detection/segmentation and image processing, with a strong background in PyTorch, TensorFlow, and OpenCV, Plus modern RAG and agentic AI LLM systems using LangChain and LangGraph. Key Expertise YOLO Object Detection & Segmentation: Custom training/tuning (YOLO v8–v12), dataset prep, evaluation, and edge AI deployment on Jetson Nano. RAG & Agentic AI: Retrieval-augmented generation with LangChain/LangGraph, vector stores (Pinecone, ChromaDB), tool use, memory, and guardrails. Recommendation AI Engine Systems. Model Deployment & Optimization: Packaging for production (REST), quantization/acceleration where applicable; VM-based deployments. Full Pipeline Development: Data collection → labeling → training → testing → Flask/FastAPI REST APIs → monitoring. MLOps & CI/CD: Experiment tracking, versioning, reproducible workflows, and automated delivery with GitHub/GitLab. API Integration & Apps: Secure API integration with third-party services; Flutter front-ends that consume ML APIs. Cloud & Storage: AWS S3 for datasets/artifacts; deployable on cloud VMs or on-prem. Frameworks & Tools PyTorch, TensorFlow/TFLite, OpenCV, scikit-learn, Pandas, NumPy LangChain, LangGraph, RAG, LLM, Pinecone, ChromaDB Flask, FastAPI (REST API deployment) Databases SQL, MySQL, PostgreSQL, Supabase GitHub, GitLab (MLOps/CI-CD) Google Colab / Jupyter Notebook AWS S3, VM-based deployments React & Flutter (client apps & dashboards)

Are you a startup founder or agency sitting on a software project that keeps breaking, stalling, or eating your budget without delivering results? 𝘐𝘴 𝘺𝘰𝘶𝘳 𝘤𝘶𝘳𝘳𝘦𝘯𝘵 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘦𝘳 𝘮𝘰𝘳𝘦 𝘧𝘰𝘤𝘶𝘴𝘦𝘥 𝘰𝘯 𝘸𝘳𝘪𝘵𝘪𝘯𝘨 𝘧𝘢𝘯𝘤𝘺 𝘤𝘰𝘥𝘦 𝘵𝘩𝘢𝘯 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘴𝘰𝘭𝘷𝘪𝘯𝘨 𝘺𝘰𝘶𝘳 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘱𝘳𝘰𝘣𝘭𝘦𝘮? Typical founders and agencies I speak to are doing well on the business side but deeply concerned about one thing. 𝑻𝒉𝒆𝒊𝒓 𝒔𝒐𝒇𝒕𝒘𝒂𝒓𝒆 𝒘𝒂𝒔 𝒏𝒆𝒗𝒆𝒓 𝒃𝒖𝒊𝒍𝒕 𝒕𝒐 𝒔𝒄𝒂𝒍𝒆. They are disappointed with systems that crack the moment traffic spikes. They are unhappy with developers who disappear after delivery leaving them with technical debt they cannot explain to their own team. ▸ 𝘋𝘰𝘦𝘴 𝘺𝘰𝘶𝘳 𝘴𝘺𝘴𝘵𝘦𝘮 𝘭𝘰𝘢𝘥 𝘭𝘪𝘬𝘦 𝘢 𝘸𝘰𝘰𝘥𝘦𝘯 𝘸𝘩𝘦𝘦𝘭 𝘦𝘷𝘦𝘳𝘺 𝘵𝘪𝘮𝘦 𝘳𝘦𝘢𝘭 𝘶𝘴𝘦𝘳𝘴 𝘴𝘩𝘰𝘸 𝘶𝘱? ▸ 𝘐𝘴 𝘪𝘵 𝘯𝘰𝘵 𝘮𝘰𝘣𝘪𝘭𝘦 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘦𝘥? ▸ 𝘋𝘰𝘦𝘴 𝘪𝘵 𝘨𝘰 𝘥𝘰𝘸𝘯 𝘦𝘹𝘢𝘤𝘵𝘭𝘺 𝘸𝘩𝘦𝘯 𝘺𝘰𝘶𝘳 𝘮𝘰𝘴𝘵 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵 𝘤𝘭𝘪𝘦𝘯𝘵𝘴 𝘢𝘳𝘦 𝘸𝘢𝘵𝘤𝘩𝘪𝘯𝘨? 𝑰𝒇 𝒕𝒉𝒂𝒕 𝒊𝒔 𝒚𝒐𝒖, 𝒕𝒉𝒆𝒏 𝒎𝒂𝒚𝒃𝒆 𝑰 𝒄𝒂𝒏 𝒉𝒆𝒍𝒑. I am a 𝗦𝗲𝗻𝗶𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 with 5+ 𝘆𝗲𝗮𝗿𝘀 of experience and 5𝟬+ 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 across SaaS platforms, MVPs, e-commerce systems, and enterprise-level infrastructure. 𝘐 𝘥𝘰 𝘯𝘰𝘵 𝘫𝘶𝘴𝘵 𝘸𝘳𝘪𝘵𝘦 𝘤𝘰𝘥𝘦. I understand your business model first. I choose the right stack strategically. I build systems engineered for 𝗴𝗿𝗼𝘄𝘁𝗵 not just quick launches and I communicate clearly so you never chase updates or wonder what is happening with your product. 𝘛𝘩𝘦𝘺 𝘭𝘢𝘶𝘨𝘩𝘦𝘥 𝘸𝘩𝘦𝘯 𝘐 𝘴𝘢𝘪𝘥 𝘐 𝘤𝘰𝘶𝘭𝘥 𝘳𝘦𝘴𝘤𝘶𝘦 𝘢 𝘧𝘢𝘪𝘭𝘪𝘯𝘨 𝘚𝘢𝘢𝘚 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘪𝘯 𝘶𝘯𝘥𝘦𝘳 30 𝘥𝘢𝘺𝘴. 𝘉𝘶𝘵 𝘸𝘩𝘦𝘯 𝘵𝘩𝘦𝘺 𝘴𝘢𝘸 𝘵𝘩𝘦 𝘳𝘦𝘴𝘶𝘭𝘵𝘴 𝒕𝒉𝒆 𝒄𝒐𝒏𝒗𝒆𝒓𝒔𝒂𝒕𝒊𝒐𝒏 𝒄𝒉𝒂𝒏𝒈𝒆𝒅. You have options. But 𝘩𝘪𝘳𝘪𝘯𝘨 𝘢 𝘭𝘰𝘸-𝘤𝘰𝘴𝘵 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘦𝘳 𝘪𝘴 𝘭𝘪𝘬𝘦 𝘭𝘰𝘷𝘦 𝘢𝘵 𝘧𝘪𝘳𝘴𝘵 𝘴𝘪𝘨𝘩𝘵. It feels good at the start. But later you open the box and sometimes 𝘵𝘩𝘦 𝘣𝘰𝘹 𝘪𝘴 𝘦𝘮𝘱𝘵𝘺. I come in with a clear process, defined standards, and long-term thinking. If the system I build does not handle your load, pass QA, and work across every device I will make it right. 𝗧𝗵𝗮𝘁 𝗶𝘀 𝗺𝘆 𝗴𝘂𝗮𝗿𝗮𝗻𝘁𝗲𝗲. 𝑰𝒇 𝒚𝒐𝒖 𝒂𝒓𝒆 𝒔𝒆𝒓𝒊𝒐𝒖𝒔 𝒂𝒃𝒐𝒖𝒕 𝒃𝒖𝒊𝒍𝒅𝒊𝒏𝒈 𝒔𝒐𝒇𝒕𝒘𝒂𝒓𝒆 𝒕𝒉𝒆 𝒓𝒊𝒈𝒉𝒕 𝒘𝒂𝒚, 𝒔𝒆𝒏𝒅 𝒎𝒆 𝒂 𝒎𝒆𝒔𝒔𝒂𝒈𝒆 𝒓𝒊𝒈𝒉𝒕 𝒏𝒐𝒘. 𝗬𝗼𝘂𝗿 𝗻𝘂𝗺𝗯𝗲𝗿 𝗼𝗻𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗽𝗮𝗿𝘁𝗻𝗲𝗿 the architect who makes sure your system never becomes your biggest bottleneck. 𝘗.𝘚. 𝘐𝘧 𝘰𝘯𝘦 𝘥𝘢𝘺 𝘺𝘰𝘶𝘳 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘢𝘤𝘩𝘪𝘦𝘷𝘦𝘴 𝘦𝘷𝘦𝘯 𝘢 𝘧𝘳𝘢𝘤𝘵𝘪𝘰𝘯 𝘰𝘧 𝘵𝘩𝘦 𝘨𝘳𝘰𝘸𝘵𝘩 𝘺𝘰𝘶 𝘢𝘳𝘦 𝘸𝘰𝘳𝘬𝘪𝘯𝘨 𝘵𝘰𝘸𝘢𝘳𝘥 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘴𝘺𝘴𝘵𝘦𝘮 𝘩𝘰𝘭𝘥𝘴 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 𝘣𝘳𝘦𝘢𝘬𝘪𝘯𝘨 𝒕𝒉𝒂𝒕 𝒊𝒔 𝒕𝒉𝒆 𝒐𝒏𝒍𝒚 𝒎𝒆𝒂𝒔𝒖𝒓𝒆 𝒐𝒇 𝒔𝒖𝒄𝒄𝒆𝒔𝒔 𝑰 𝒄𝒂𝒓𝒆 𝒂𝒃𝒐𝒖𝒕. 𝗙𝗔𝗤 𝗖𝗮𝗻 𝘆𝗼𝘂 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗰𝗼𝗱𝗲𝗯𝗮𝘀𝗲𝘀? Both new and existing. 𝘐 𝘥𝘰 𝘯𝘰𝘵 𝘳𝘦𝘸𝘳𝘪𝘵𝘦 𝘧𝘰𝘳 𝘵𝘩𝘦 𝘴𝘢𝘬𝘦 𝘰𝘧 𝘳𝘦𝘸𝘳𝘪𝘵𝘪𝘯𝘨. 𝗪𝗵𝗮𝘁 𝘀𝘁𝗮𝗰𝗸𝘀 𝗱𝗼 𝘆𝗼𝘂 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵? React, Next.js, Node.js, Python, WordPress, AWS, GCP, PostgreSQL, MongoDB and more. 𝘛𝘩𝘦 𝘴𝘵𝘢𝘤𝘬 𝘪𝘴 𝘢𝘭𝘸𝘢𝘺𝘴 𝘤𝘩𝘰𝘴𝘦𝘯 𝘣𝘢𝘴𝘦𝘥 𝘰𝘯 𝘺𝘰𝘶𝘳 𝘯𝘦𝘦𝘥𝘴 not my preference. 𝗖𝗮𝗻 𝘆𝗼𝘂 𝗵𝗮𝗻𝗱𝗹𝗲 𝗯𝗼𝘁𝗵 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗮𝗻𝗱 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁? Yes. I lead execution and stay involved through delivery 𝘐 𝘥𝘰 𝘯𝘰𝘵 𝘤𝘰𝘯𝘴𝘶𝘭𝘵 𝘢𝘯𝘥 𝘥𝘪𝘴𝘢𝘱𝘱𝘦𝘢𝘳. 𝗪𝗵𝗮𝘁 𝗶𝗳 𝗜 𝗼𝗻𝗹𝘆 𝗻𝗲𝗲𝗱 𝗮 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗿𝗲𝘃𝗶𝗲𝘄? That is a standalone service. Send me a message and we can start there. 𝑰𝒇 𝒂𝒏𝒚 𝒐𝒇 𝒕𝒉𝒂𝒕 𝒊𝒔 𝒘𝒉𝒂𝒕 𝒚𝒐𝒖 𝒏𝒆𝒆𝒅 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝗺𝗲 𝗮𝗻𝗱 𝗹𝗲𝘁 𝘂𝘀 𝗴𝗲𝘁 𝘁𝗼 𝘄𝗼𝗿𝗸.

I help startups, founders, and teams bridge the gap between AI hype and production-ready business value So far i have: ● Helped clients raise $3M+ through AI-powered growth ● Built 30+ AI systems, ● Drove a 17% revenue increase in 7 months for a US startup ● Helped products impact 300,000+ users ● Delivered 90+ successful projects on Upwork I operate as a strategic technology partner Most founders come to me when: - they have an AI idea but don't know what should be built first - their prototype works in demos but breaks with real users - they need an investor-ready MVP quickly - their team wastes hours on manual workflows - they want AI integrated into existing system My job is not just to "build with AI." It is to help you figure out what should be built, and how to make it good enough that real users keep coming back I help you build: ✅ Investor-ready AI proof of concepts ✅ MVPs and v1 AI products ✅ RAG apps and knowledge copilots ✅ AI agents and workflow automation ✅ Chatbots that answer from real company data ✅ Internal tools that save time and cut manual work My core stack include: OpenAI, Claude, Gemini, LangGraph, LangChain, CrewAI, FastAPI, Python, PostgreSQL, Pinecone, Qdrant, AWS, Docker, Next.js, React, N8n, Zapier The best AI product is the one that solves the right problem using the right data architecture I scope all project architecture, data flows, and development milestones before a single line of code is written, ensuring predictable timelines and clear pricing transparency upfron If you have an AI concept and want to transform it into a highly reliable, revenue-driven system - LET'S TALK ---------------- -------------------------- ------------------- 

-- Top 3% of AI Developers on Upwork (rated: Top Rated Plus) -- 5+ Years of Professional Experience in Machine Learning -- Specialized in Generative AI, Image Generation, and Speech Generation As a specialist in AI, I bring a strong theoretical foundation alongside practical expertise in machine learning, deep learning, and generative AI models. With over 5 years of experience, I excel in applying advanced AI techniques to solve complex problems in image generation, speech synthesis, and more. Key Areas of Expertise: - Deep expertise in generative AI models for image, video, and speech generation (GANs, VAEs, diffusion models). - Skilled in designing and fine-tuning LLMs and multimodal models, integrating image, text, and speech for advanced AI solutions. - Proficient in the full ML/DL pipeline: architecture design, model training, deployment, and continuous optimization. - Extensive experience in applying cutting-edge neural networks for computer vision, NLP, and audio processing. - Developed custom generative models for use cases including text-to-image, image-to-image, speech-to-text, text-to-speech, and voice cloning. - Implemented solutions for automated content generation, image captioning, visual understanding, speech synthesis, and multimodal fusion. - Focused on optimizing models for deployment on mobile, cloud, and edge devices using tools like PyTorch, TensorFlow, and NVIDIA frameworks. Research Experience: - Published work in reinforcement learning at ICML ("Inverse Constrained Reinforcement Learning") with applications in human feedback for improving generative models. - Expertise in Reinforcement Learning from Human Feedback (RLHF), a key technique used in training high-performance LLMs and generative models. Technical Skills: - Core Areas: Generative AI, Image Generation, Speech Generation, Multimodal AI, Computer Vision, NLP, OCR, Large Language Models, Big Data Analytics. - Libraries/Frameworks: TensorFlow, Keras, PyTorch, Hugging Face, OpenAI, CoreML, FastAPI, Flask. - Toolkits: PyTorch, Numpy, Pandas, CUDA, TensorFlow, OpenCV, Tflite. - Operational Tools: GCP, AWS, Kubernetes, Docker, Github, Gitlab.

I am a Machine Learning Engineer with four years of experience working across deep learning research, large scale AI systems, and production model deployment. Over the years, I have worked extensively in medical imaging, computer vision, NLP, signal processing, and large language models, building systems that range from experimental research pipelines to deployed real world AI applications. My day to day work primarily involves Python, PyTorch, TensorFlow, Keras, HuggingFace Transformers, sentence transformers, scikit learn, OpenCV, Pandas, and NumPy. I enjoy working deeply on both the research and engineering sides of machine learning, especially problems that require understanding model behavior rather than simply applying existing architectures blindly. A large part of my background is research driven. I have authored multiple peer reviewed publications in indexed journals and IEEE conferences, including publications in Neurocomputing, Healthcare Analytics, Engineering Applications of Artificial Intelligence, Telematics and Informatics Reports, and other Elsevier and IEEE venues. My research has focused heavily on explainable AI, healthcare AI, and advanced deep learning systems. Some of my published work includes CARDxnosis, an explainable knowledge driven framework for ECG diagnosis and clinical report generation, an explainable AI system for trustworthy arrhythmia detection, a CNN RNN Attention hybrid architecture for automatic modulation classification, ensemble deep learning approaches for lung cancer detection from CT scans, and SRGAN based white blood cell image generation and classification pipelines. Alongside published work, I am currently involved in research on brain tumor segmentation, ADHD and ASD classification from brain connectome graphs, epileptic seizure prediction from EEG signals, and interpretable tabular learning using graph neural networks combined with Kolmogorov Arnold Networks. Beyond research, I have substantial hands on experience building and deploying production grade AI systems. One of my major recent projects was LaborBERT v4, a domain adaptive transformer fine tuning system processing hundreds of thousands of records through a large scale training pipeline. The project involved multiple experimental setups including contrastive learning, masked language model pretraining, temporal contrastive learning, cross attention based fusion, multi task training, and Matryoshka Representation Learning. I have also built hybrid embeddings plus LLM systems for taxonomy mapping using OpenAI embeddings alongside locally hosted LLaMA and Mistral models through Ollama. In addition, I have worked on deployed clinical AI systems and a portable on device diagnostic AI solution with embedded deep learning models for point of care inference, which gave me valuable experience in optimization, deployment constraints, inference design, and production reliability. My broader project portfolio includes vehicle detection using Mask R CNN, human activity recognition on the Kinetics 700 dataset, facial keypoint detection with MultiRes UNet, semantic segmentation pipeline redesign, Stable Diffusion based image editing workflows, toxic comment classification, RASA based conversational AI systems, and large scale scraping and automation pipelines using Playwright and Selenium. I have also worked with Flask and Django based deployment pipelines and cloud hosted ML systems. From an engineering perspective, I care strongly about clean and maintainable systems. I follow disciplined workflows involving modular code design, Git based version control, reproducible experimentation, structured evaluation, bootstrap validated metrics, and detailed documentation. I am also comfortable preparing scientific reports, research papers, and journal submissions using both LaTeX and Word. What ties all of this together is that I genuinely enjoy solving difficult technical problems, especially the kind that require balancing research depth with practical engineering constraints. I am most motivated by projects where thoughtful experimentation, careful system design, and real world usability matter equally.