Hire the Best RAG Developers

Your AI project shouldn't break the moment real users hit it. I build AI SaaS platforms that handle 100K+ users, respond in <200ms, and generate real revenue — not demos that fall apart in production. SHIPPED PROJECTS → Legal RAG Platform: Serves 100K+ users, cut support queries 60%, running 18+ months → Multi-LLM Chatbot Builder: Chatbase-style SaaS with OpenAI/Claude/Gemini + Stripe billing → Multi-Tenant AI Agent Platform: Full SaaS with team workspaces, usage tracking, white-label ready → Voice AI Phone System: Vapi + N8N + Mindbody — handles real inbound calls and books appointments → AI CRM Booking System: GoHighLevel + OpenAI integration for automated calendar scheduling → Memory-Evolving Chat: Behavioral adaptation system that learns user patterns over time → AI Research Agent: LangGraph-powered web research with structured output → Vapi Dashboard: Real-time agent monitoring with Supabase + webhooks → CI/CD Pipeline: Full DevOps setup for startup — "the kind of engineer every startup wants" (client quote) → Internal Knowledge Assistants: RAG systems for company documents and support automation --- WHAT I BUILD • AI SaaS Products — Full platforms with auth, billing, dashboards, analytics, multi-tenancy • RAG & LLM Pipelines — Grounded retrieval with Pinecone, Weaviate, Chroma, pgvector • Voice AI & Automation — Vapi agents, N8N workflows, CRM integrations • Production Infrastructure — AWS, Docker, CI/CD pipelines, monitoring FULL STACK AI/LLM: LangChain | LangGraph | LlamaIndex | CrewAI | OpenAI | Claude | Gemini | AWS Bedrock Voice AI: Vapi | Twilio | ElevenLabs Automation: N8N | Make | Zapier Backend: Python | FastAPI | Django | Node.js | Express Frontend: Next.js | React | TypeScript | TailwindCSS Databases: PostgreSQL | Supabase | Redis | MongoDB | Pinecone | Weaviate | Chroma Integrations: Stripe | GoHighLevel | Mindbody | HubSpot | Slack | Resend Cloud/DevOps: AWS (ECS, Lambda, S3, Bedrock, EC2) | GCP | Docker | GitHub Actions | CI/CD HOW I WORK • Direct communication, weekly progress updates • Architecture mapped before code starts

𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 & 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 | 8+ 𝗬𝗲𝗮𝗿𝘀 | 𝟭% 𝗼𝗳 𝗨𝗽𝘄𝗼𝗿𝗸 | 𝟭𝟬𝟬% 𝗝𝗼𝗯 𝗦𝘂𝗰𝗰𝗲𝘀𝘀. ✅ $300K+ Total earnings ✅8+ Years experience as Fullstack Developer ✅ 80+ Projects Completed. ✅Top Rated Plus. ✅ 100% Job Success Rate. ✅ AWS certified ✅ Python certified ✅50hrs/week available ✅ 4+ AI/ML Integrations 🔴 I am in the 𝗧𝗼𝗽 𝟭% overall on Upwork. 🔴 I am in the 𝗧𝗼𝗽 𝟰% overall on Stack Overflow. 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭 / 𝐕𝐨𝐢𝐜𝐞 𝐀𝐠𝐞𝐧𝐭𝐬: 𝐂𝐫𝐞𝐰𝐀𝐈 / 𝐀𝐮𝐭𝐨𝐆𝐞𝐧 / 𝐀𝐦𝐚𝐳𝐨𝐧 𝐏𝐨𝐥𝐥𝐲 / 𝐃𝐞𝐞𝐩𝐠𝐫𝐚𝐦 / 𝐑𝐚𝐬𝐚 𝐀𝐈 / 𝐑𝐢𝐯𝐞𝐫𝐬𝐢𝐝𝐞 𝐒𝐃𝐊 / 𝐀𝐳𝐮𝐫𝐞 𝐀𝐈 𝐒𝐩𝐞𝐞𝐜𝐡/𝐋𝐋𝐌 𝐅𝐢𝐧𝐞𝐭𝐮𝐧𝐢𝐧𝐠: 𝐔𝐬𝐢𝐧𝐠 𝐏𝐄𝐅𝐓 / 𝐋𝐨𝐑𝐀 / 𝐐𝐋𝐨𝐑𝐀 / 𝐑𝐋𝐇𝐅 / 𝐃𝐏𝐎 / 𝐒𝐅𝐓 𝐰𝐢𝐭𝐡 𝐔𝐧𝐬𝐥𝐨𝐭𝐡 / 𝐀𝐱𝐨𝐥𝐨𝐭𝐥 / 𝐇𝐮𝐠𝐠𝐢𝐧𝐠𝐅𝐚𝐜𝐞 𝐀𝐮𝐭𝐨𝐓𝐫𝐚𝐢𝐧 / 𝐒𝐚𝐠𝐞𝐌𝐚𝐤𝐞𝐫 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠/𝐎𝐩𝐞𝐧-𝐒𝐨𝐮𝐫𝐜𝐞 𝐋𝐋𝐌𝐬: 𝐋𝐋𝐀𝐌𝐀 𝟑 / 𝐌𝐢𝐬𝐭𝐫𝐚𝐥 𝟕𝐁 / 𝐌𝐢𝐱𝐭𝐫𝐚𝐥 𝟖𝐱𝟕𝐁 / 𝐅𝐚𝐥𝐜𝐨𝐧 / 𝐆𝐞𝐦𝐦𝐚 / 𝐁𝐥𝐨𝐨𝐦 / 𝐎𝐫𝐜𝐚 𝐌𝐢𝐧𝐢 / 𝐆𝐮𝐚𝐧𝐚𝐜𝐨/𝐅𝐚𝐬𝐭 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞: 𝐯𝐋𝐋𝐌 / 𝐓𝐆𝐈 / 𝐓𝐞𝐧𝐬𝐨𝐫𝐑𝐓-𝐋𝐋𝐌 / 𝐒𝐊𝐏𝐢𝐥𝐨𝐭/𝐏𝐫𝐨𝐦𝐩𝐭 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: 𝐌𝐮𝐥𝐭𝐢-𝐭𝐮𝐫𝐧 / 𝐅𝐞𝐰-𝐬𝐡𝐨𝐭 / 𝐙𝐞𝐫𝐨-𝐬𝐡𝐨𝐭 / 𝐑𝐀𝐆-𝐁𝐚𝐬𝐞𝐝 / 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐚𝐛𝐥𝐞 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬/𝐐𝐮𝐚𝐧𝐭𝐢𝐳𝐚𝐭𝐢𝐨𝐧: 𝐀𝐖𝐐 / 𝐆𝐏𝐓𝐐 / 𝐆𝐆𝐔𝐅 / 𝐆𝐆𝐌𝐋 / 𝐐𝐋𝐎𝐑𝐀 / 𝐏𝐓𝐐 / 𝐃𝐐/𝐑𝐀𝐆 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 & 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: 𝐋𝐚𝐧𝐠𝐂𝐡𝐚𝐢𝐧 / 𝐋𝐥𝐚𝐦𝐚𝐈𝐧𝐝𝐞𝐱 / 𝐂𝐡𝐫𝐨𝐦𝐚 / 𝐅𝐀𝐈𝐒𝐒 / 𝐏𝐢𝐧𝐞𝐜𝐨𝐧𝐞 / 𝐐𝐝𝐫𝐚𝐧𝐭 / 𝐖𝐞𝐚𝐯𝐢𝐚𝐭𝐞 / 𝐌𝐢𝐥𝐯𝐮𝐬 Greetings! I am Atul Kumar, a seasoned developer with over 8+ years of experience in web application and software development. Working with LLMs for the past 8+ years and have good expertise in AI Agents development using langchain, LlamaIndex, and LLMs like Claude, GPT4o, Amazon Bedrock, Ollama 🔹 AI Agents / Voice Agents: CrewAI, AutoGen, Amazon Polly, Deepgram, Rasa AI 🔹 LLM Fine-tuning: PEFT, LoRA, QLoRA, RLHF, DPO with Unsloth, Axolotl, HuggingFace AutoTrain 🔹 Open-Source LLMs: LLaMA 3, Mistral 7B, Mixtral 8×7B, Falcon, Gemma 🔹 Inference Optimization: vLLM, TGI, TensorRT-LLM 🔹 Prompt Engineering: Multi-turn, Few-shot, Zero-shot, RAG-based prompts 🔹 Quantization: AWQ, GPTQ, GGUF, GGML 🔹 RAG Systems: LangChain, LlamaIndex, ChromaDB, FAISS, Pinecone, Qdrant 🔹 Data Pipeline: Synthetic dataset generation, LLM evaluation frameworks 🔹 LLM Deployment: AWS Sagemaker, RunPod, GCP AI Platform, Vercel AI SDK 🖥️ 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀: 🔹 Proficient in Node.js, Express.js, Python, Django, Flask, AWS Lambda for backend API. 🔹 Experienced with relational & NoSQL databases: MySQL, PostgreSQL, MongoDB, Firebase, Firestore. 🔹 Skilled in Python FastAPI, REST API, GraphQL API development, and database schema design. 🔹 Knowledgeable in Redis, Docker, Kubernetes, AWS EC2, S3, Nginx for scalable infrastructure. 🔹 Experienced with Nest.js for enterprise-grade server-side applications. 🔹 LangChain, LangServe, LangSmith, HuggingFace, Transformers for AI/LLM integrations. 🔹 Vector Databases: Chroma, FAISS, Pinecone, Qdrant for RAG pipelines. 🔹 Low-code AI tools: Flowise AI, LangFlow, StackAI for rapid prototyping. 🔹 Familiar with Celery task queues, testing frameworks (Pytest, Unittest), and automation tools like Selenium. 🌐 𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀: 🔹 Proficient in TypeScript, Redux Toolkit, Tailwind CSS with Next.js for high-performance frontends. 🔹 Skilled in building Progressive Web Apps (PWA) and Single Page Applications (SPA). 🔹 Expert in Vue.js, Nuxt.js, React.js, Next.js, HTML5, CSS3, React Native for responsive and cross-platform UIs. 🛠️ 𝗧𝗼𝗼𝗹𝘀 & 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: 🔹 Skilled in Python ML libraries: Scikit-learn, Numpy, Pandas, Matplotlib, Seaborn. 🔹 Familiar with OpenAI APIs, Whisper, GPT models, ChatGPT integration, and AI chatbot deployment. 🔹 Experienced with AWS (Lambda, S3, EC2, Sagemaker), Git/GitHub, and Linux environments (Ubuntu, CentOS). 🌟 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗜 & 𝗟𝗟𝗠 𝗦𝗸𝗶𝗹𝗹𝘀: 🔹 AI Agents / Voice Assistants: CrewAI, AutoGen, Amazon Polly, Deepgram, Rasa AI. 🔹 Open-Source LLMs: LLaMA 3, Mistral 7B, Mixtral 8×7B, Falcon, Gemma. 🔹 Inference Optimization: vLLM, TGI, TensorRT-LLM for high-speed deployments. 🔹 Prompt Engineering: Multi-turn, Few-shot, Zero-shot, RAG-based prompts. 🔹 Quantization: AWQ, GPTQ, GGUF, GGML for efficient LLM deployment. 🔹 LLM Fine-tuning: PEFT, LoRA, QLoRA, RLHF, DPO with Unsloth, Axolotl, H My expertise spans both frontend and backend technologies, as well as a variety of tools and additional skills that enable me to deliver comprehensive solutions. I am dedicated to providing high-quality, efficient solutions that cater to the unique needs of each project. My diverse skill set allows me to approach challenges from multiple angles, ensuring robust and innovative solutions. Warm regards, Atul Kumar

𝗜 𝗯𝘂𝗶𝗹𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗿𝗲𝗮𝗱𝘆 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗽𝗮𝘆 𝗳𝗼𝗿 𝘁𝗵𝗲𝗺𝘀𝗲𝗹𝘃𝗲𝘀: I saved a fintech client €𝟰𝟬,𝟬𝟬𝟬 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 by automating their KYC pipeline (𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆) and cut clinical documentation time by 𝟲𝟬% with an AI medical scribe inside a live EMR platform. If you have messy documents, manual workflows, or an agent or chatbot idea that needs to actually work in production, not just in a demo, I can ship it fast without sacrificing accuracy or scalability. 𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗 🔹 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 & 𝗠𝘂𝗹𝘁𝗶 𝗔𝗴𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: autonomous, decision making agents with LangChain, LangGraph and CrewAI that automate real backend processes: document review, support, lead handling, internal ops. 🔹 𝗥𝗔𝗚 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀: retrieval augmented generation chatbots over your PDFs, docs and databases. Hybrid GraphRAG (Neo4j) plus vector search for grounded, accurate answers with strict guardrails against hallucination. 🔹 𝗢𝗖𝗥 & 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗔𝗜: invoice, ID and form data extraction with PaddleOCR, AWS Textract, YOLO and LayoutLM. 𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 on IDs, invoices, tables and unstructured documents. 🔹 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗔𝗜 & 𝗘𝗠𝗥 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: HIPAA compliant medical scribes (Whisper speech to text, speaker diarization, auto generated SOAP notes and ICD 10 codes), wound analysis computer vision, clinical RAG with PII redaction. 🔹 𝗞𝗬𝗖 & 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: document localization, MRZ parsing, ArcFace biometric matching, liveness detection, real time transaction risk engines. 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 𝗖𝗟𝗜𝗘𝗡𝗧𝗦 𝗣𝗔𝗜𝗗 𝗙𝗢𝗥 €𝟰𝟬𝗞 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 𝘀𝗮𝘃𝗲𝗱: automated fintech KYC pipeline (OCR plus face match plus verification agents) 𝟲𝟬% 𝗹𝗲𝘀𝘀 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗶𝗺𝗲: AI medical scribe running in a production EMR 𝟰𝟬% 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝘂𝗽𝗹𝗶𝗳𝘁: hybrid GraphRAG retrieval for complex financial queries 𝟭𝟬𝘅 𝗳𝗮𝘀𝘁𝗲𝗿 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: logistics and finance workflows 𝗦𝘂𝗯 𝟮𝟬𝟬𝗺𝘀 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗹𝗮𝘁𝗲𝗻𝗰𝘆: FastAPI microservices with Redis caching 𝗧𝗘𝗖𝗛 𝗦𝗧𝗔𝗖𝗞 Python, FastAPI, Docker, AWS, GCP | LangChain, LangGraph, CrewAI, OpenAI, Claude, Hugging Face | Pinecone, FAISS, Weaviate, Neo4j, MongoDB, Redis | OpenCV, YOLO, PaddleOCR, Tesseract, LayoutLM | PyTorch, TensorFlow 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 Fast execution with production discipline: clear milestones, regular updates, clean documented code, containerized deployment. I use modern AI dev tooling (including Claude Code) to ship in days what normally takes weeks, without cutting corners on architecture. If you want an AI system that works in production, send me an invite or message and let's scope it in a quick call. 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀: AI Engineer, AI Agent Developer, AI Agents, Multi Agent Systems, RAG, Retrieval Augmented Generation, Chatbot Development, LLM Integration, GPT 4o, Claude, LangChain, LangGraph, CrewAI, OCR, Document AI, Data Extraction, Computer Vision, Healthcare AI, EMR Automation, KYC Automation, Identity Verification, NLP, Python, FastAPI

I build production-grade AI agents and multi-agent systems that run reliably in production, not just in demos. If you need agents that reason, use tools, and execute multi-step tasks autonomously, that is my core focus. 10+ years in software engineering, now fully focused on agentic AI. I cover the full stack of modern agent engineering, from protocol-level coordination to deployed SaaS and mobile products. ─── AGENTIC AI & ORCHESTRATION ─── → Agent harness architecture: OpenHarness, OpenClaw, MiniClaw, Hermes Agent → Conversational agent pipelines: OpenJarvis → Multi-agent systems: LangChain, LangGraph, CrewAI, AutoGen → MCP (Model Context Protocol): server design, tool registration, context routing → A2A (Agent-to-Agent), ACP, and A2UG protocol implementations → Pi.dev agent runtime and SDK integration → Agentic patterns: ReAct, Plan-and-Execute, Reflection, Tool Use ─── LLM & RAG ─── → RAG pipelines: ChromaDB, Pinecone, pgvector → LLM integration: OpenAI, Anthropic Claude, Groq, Ollama, Mistral → Fine-tuning, prompt engineering, structured output design → Embedding pipelines and semantic retrieval ─── SAAS & AUTOMATION ─── → AI-native backends: FastAPI, Node.js, Python → Workflow automation: n8n with agent-triggered pipelines → Web and mobile delivery: React, React Native, Flutter I work with startups and product teams who need more than a chatbot, teams building real systems where multiple agents collaborate and get work done end to end. Message me with what you are trying to automate or build, and I will tell you straight whether agents are the right call and how I would approach it. I have 100% Job Success | Top Rated Agency | CTO, ArmorTech & HTML5Solutions

I am the Top 3 percent developer on Upwork having Pink badge, I help clients build products that are sharp, scalable, and results focused. I design and build production-grade AI systems powered by Large Language Models, Retrieval-Augmented Generation, intelligent chatbots, and autonomous multi-agent architectures that go beyond prototypes and deliver measurable business outcomes. My expertise lies in combining advanced AI modeling with scalable system design, enabling chatbots, agents, and multi-agent systems to operate reliably in real-world environments. 🔹 Core Expertise Generative AI Systems LLM integration using OpenAI, Gemini, Claude, and open-source models like LLaMA and Mistral Prompt engineering for deterministic outputs, structured responses, and controlled reasoning Tool-augmented generation and function calling for real-world execution Context management for long conversations and memory-aware systems RAG & Knowledge Systems End-to-end RAG pipelines with vector databases like Pinecone, FAISS, Weaviate Hybrid retrieval combining semantic search, keyword search, and metadata filtering Context optimization like chunking strategies, re-ranking, and compression Knowledge grounding for chatbots and AI assistants to reduce hallucinations AI Chatbots (Advanced) Conversational AI with multi-turn memory and contextual awareness Domain-specific chatbots for customer support, internal tools, and SaaS platforms Stateful chat systems with session memory and retrieval-backed responses Integration with APIs, CRMs, and external tools for actionable conversations AI Agents & Multi-Agent Systems Autonomous AI agents with task planning, reasoning, and tool usage Multi-agent orchestration where agents collaborate, delegate, and validate outputs Workflow automation agents for tasks like lead qualification, research, and execution Event-driven agent systems with feedback loops and self-correction Machine Learning & Deep Learning NLP pipelines, embeddings, and similarity search systems Fine-tuning and domain adaptation for LLMs Recommendation systems and predictive modeling Evaluation frameworks for model performance and reliability 🔹 System Design & Engineering I focus on building end-to-end AI architectures where chatbots and agents are part of a larger, reliable system. Backend systems using Python, FastAPI, Node.js Scalable architectures for chatbot platforms and agent workflows Vector database optimization and retrieval latency tuning Real-time inference systems for conversational AI Secure integrations with third-party APIs and enterprise systems MLOps & AI Infrastructure Deployment on AWS, GCP, Azure with GPU scaling CI/CD pipelines for AI systems and agent workflows Monitoring, logging, and observability for chatbot and agent performance Cost optimization for LLM-heavy applications 🔹 What I Build Intelligent AI chatbots with deep contextual understanding and action capabilities RAG-powered knowledge assistants for enterprises and SaaS products AI agents that automate workflows like lead qualification, support, and operations Multi-agent systems for complex task orchestration and decision-making Document intelligence systems for extraction, summarization, and structured insights AI copilots integrated into products for enhanced user experience 🔹 My Approach I design systems where chatbots and agents are not just interfaces, but intelligent decision layers. Focus on accuracy, latency, and cost trade-offs Build for edge cases and unpredictable inputs Ensure structured outputs for downstream systems Design modular architectures for scaling from single-agent to multi-agent systems 🔹 Differentiation Deep expertise in both LLMs and system-level architecture Experience building real-world chatbot and agent-based systems Strong understanding of multi-agent coordination and workflow automation Ability to convert complex ideas into scalable AI products Product-focused mindset with emphasis on measurable impact 🔹 Tech Stack Python, FastAPI, Node.js, LangChain, LlamaIndex, Pinecone, FAISS, Weaviate, OpenAI, Gemini, Claude, Hugging Face, Docker, Kubernetes, AWS, GCP If you are looking to build advanced AI chatbots, intelligent agents, or multi-agent systems, I can help you design and implement solutions that are technically robust and production-ready. Let us build systems that think, act, and scale.

Most AI initiatives are not unsuccessful because of substandard models. They are not working after all no one assembles all the pieces together. 𝐓𝐡𝐚𝐭'𝐬 𝐦𝐲 𝐣𝐨𝐛. ᯓ★ I build production-ready AI systems that solve real business problems. 🌍 Serving clients globally with 𝐟𝐥𝐞𝐱𝐢𝐛𝐥𝐞 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 across all time zones 🏆 3+ years of hands-on experience across full-stack 𝐀𝐈 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 😊 Trusted by 𝟐𝟎+ 𝐜𝐥𝐢𝐞𝐧𝐭𝐬 across healthcare, legal, finance, and education 🔝 Specialized in 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 from concept to deployment Most AI projects do not fail because the model is weak. They fail because the full system is not designed properly: retrieval is poor, APIs are fragile, the frontend is disconnected, or deployment is ignored. My work focuses on connecting all of those pieces into one reliable product. I work across the full stack of AI development: machine learning/deep learning models, computer vision/NLP techniques, GenAI/Agentic AI & LLM applications, RAG pipelines, backend APIs, frontend interfaces, databases, and cloud deployment. I have built AI solutions across healthcare, legal tech, education, analytics, and cybersecurity, including systems for clinical triage, legal document analysis, real-time sentiment analysis, and enterprise knowledge assistants. ➥ Core Expertise Machine Learning: Classification, regression, clustering, dimensionality reduction, feature engineering, ensemble learning, anomaly detection, time-series, model evaluation (ROC-AUC, F1, RMSE), pipeline optimization. Deep Learning: CNNs, RNNs, LSTMs, Transformers, attention mechanisms, transfer learning, fine-tuning, backpropagation, gradient descent, model quantization. Computer Vision: Image classification, object detection, segmentation, OCR, pose estimation, preprocessing, augmentation, visual embeddings, video analysis, Grad-CAM. NLP: Text classification, sentiment analysis, NER, topic modeling, summarization, question answering, machine translation, semantic search, embedding-based retrieval. GenAI / Agentic AI: RAG pipelines, multi-agent systems, tool/function calling, prompt engineering, embeddings & vector search, reranking, hallucination reduction, LLM evaluation, fine-tuning (LoRA/QLoRA). Deployment: Containerization, orchestration, CI/CD pipelines, autoscaling, monitoring & logging, GPU deployment, serverless architecture. Full-Stack AI Development: AI chatbots, copilots, document Q&A systems, RAG-based systems, multi-agent workflows, memory systems, local LLM deployment. ➥ Tools and Frameworks Machine Learning: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, NumPy, pandas, MLflow, Optuna. Deep Learning: PyTorch, TensorFlow, Keras, Hugging Face Transformers Computer Vision: OpenCV, PyTorch Vision, Detectron2, YOLO, Albumentations, MediaPipe, Segment Anything (SAM), FiftyOne. NLP: BERT, RoBERTa, T5, GPT, SentenceTransformers, spaCy, NLTK, Hugging Face Transformers. GenAI / Agentic AI: OpenAI API, Gemini, LLaMA, Mistral, Claude, LangChain, LangGraph, CrewAI, LlamaIndex, FAISS, ChromaDB, Pinecone, Milvus, Ollama, vLLM. Backend APIs: FastAPI, Flask, Django, Node.js, GraphQL, REST APIs, Redis, Nginx, PostgreSQL/Supabase, Firebase. Deployment: Docker, Kubernetes, AWS, GCP, Azure, Vercel, GitHub Actions. ➥ Why Clients Work With Me - I build complete AI products, not just isolated models - I focus on real-world usability, performance, and maintainability - I communicate clearly and give realistic technical direction - I write clean, documented code that teams can extend - I can take a project from idea to deployment If you need an AI engineer who can handle the full pipeline from LLMs and ML models to backend, frontend, and deployment, I would be glad to help. Let’s have a quick chat/meeting and discuss the solution to your problem. ➥ EXPERTISE Machine Learning | Deep Learning | Generative AI | Agentic AI | NLP | AI System | AI Development | AI Full-stack Development | AI MVPs | Python Scripting | Computer Vision | Sentiment Analysis | RAG Chatbots | Automations | Backend Development | Frontend Development | AI Chatbots | LLM Applications | AI Web App Development | AI Engineer | Cloud Deployment | Classifications | Recommendation systems | EDA | Feature Engineering | Time-series | Predictive Modelling | MLOps | PDF Extraction | Data Extraction | Object Detection | Model Fine-tunning | AI Model Integration | AI PDF Extraction | Statistical analysis | Legal | Finance | Healthcare | Education | AI Model Development | Full-stack Development