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I don't just wrap APIs. I build the algorithms underneath them. I'm an AI engineer with 8+ years across quantum-simulation ML, fintech, EdTech, and clinical research — and an MS in Theoretical Chemistry. I train transformers from scratch, invent production retrieval algorithms, and ship AI inside a $660M global Clinical Research Organization where "almost right" doesn't pass. If your last contractor handed you a LangChain demo and called it a product, we should talk. 🔹 What Sets Me Apart ✅ Inventor of the Fox-Search Algorithm — a hybrid vector + graph retrieval method I built for asymmetric query/target search (short questions against 200-page clinical protocols). Pairs a trainable ~0.3B-parameter BERT-tier model with FAISS where pure embedding search collapses. ✅ I train my own models — fine-tuning a 0.3B encoder is normal work for me, not outsourced to a Hugging Face checkpoint. ✅ Scientific rigor — career started predicting atomistic energies and forces for ab-initio-quality molecular simulations. Same measurable-accuracy discipline now applied to LLM systems. ✅ Founder of edup.ai — autonomous grading of handwritten STEM work: computer vision + handwriting recognition + math reasoning + rubric generation, end-to-end. ✅ Production AI in a regulated industry — currently building document intelligence at Worldwide Clinical Trials (2,900+ employees, 52 countries). 🔹 Core Capabilities ▪ RAG done right — hybrid vector+graph retrieval, FAISS at scale, embedding fine-tuning, evaluation harnesses that actually measure quality. If your RAG hallucinates, I can usually tell you why within an hour. ▪ LLM engineering — self-optimizing prompt primitives that improve over time, constrained generation, tool calling, structured outputs. GPT-4o, Claude, Llama, Mistral. ▪ Document intelligence — production parsers for PDF, DOCX, XLSX with section-aware XML processing; semantic search that finds alternative phrasings of previously-approved language. ▪ Custom model training — BERT-tier encoders, LoRA/QLoRA fine-tuning, domain-adaptive pretraining. ▪ Computer vision — handwriting recognition, OCR, ViT/CLIP, math symbol understanding. ▪ High-performance engineering — C++ on the hot path, FastAPI services, real async Python. 🔹 Tech Stack • Languages: Python, C++, JavaScript / TypeScript • ML / DL: PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, NumPy, Pandas • LLM: OpenAI GPT-4o / o-series, Claude, Llama, Mistral, LangChain, LangGraph, LlamaIndex, LoRA / QLoRA, RAG, function calling • Retrieval: FAISS, Pinecone, Weaviate, Chroma, Qdrant, custom hybrid vector+graph search • Vision: OpenCV, PyTorch Vision, ViT, CLIP, OCR, handwriting recognition • Backend: FastAPI, Flask, Docker, REST, WebSockets, async Python • Frontend: Svelte 4, React • Enterprise: Microsoft Entra ID, SharePoint, Azure, AWS, GCP 🔹 Shipped Projects ▪ Fox-Search RAG — hybrid vector+graph retrieval running in production for clinical document Q&A, outperforming pure embedding baselines on long-form documents. ▪ Self-optimizing prompt infrastructure — reusable LLM primitives that improve over time without manual prompt-tuning. ▪ Document intelligence backend — parses Excel/DOCX/PDF with section-level XML comprehension; powers cross-document semantic search. ▪ RFI automation for clinical trials — ingests Excel-based Requests for Information and routes them through automated answer pipelines. ▪ edup.ai — 7-stage autonomous grading pipeline for handwritten math, from photo capture to gradebook. Live at edup.ai. ▪ Neural network potentials — ML approximations of quantum-mechanical energy surfaces for molecular simulation (same problem class as DeepMind's AlphaFold lineage). 🔹 How I Work ✔ I scope honestly — if your problem doesn't need AI, I'll tell you. ✔ I write the evaluation code before the model code. Anyone can demo; I deliver something you can measure. ✔ I ship in weekly increments — no six-week silence followed by a "big reveal." ✔ I write maintainable code your team can own after I'm gone. 🔹 Best Fit For Teams stuck on "our RAG kinda works but hallucinates" • Document-heavy domains (clinical, legal, scientific, financial, EdTech) • Startups needing a senior engineer who can architect, train, deploy, and operate • Anyone whose roadmap requires training models, not just prompting them. Send me your problem — not your solution. I'll reply within 24 hours with an honest read on whether I'm the right engineer for it.

I build production-grade GenAI systems for Fortune 500 enterprises including Verizon and PNC, : AI agents, RAG platforms, semantic layers, knowledge graphs, text-to-SQL/NLQ systems, and full-stack AI applications. I have 9+ years of experience across machine learning, computer vision, NLP, backend engineering, and full-stack product development. Recently, I have led large engineering teams building enterprise AI platforms for telecom and banking use cases. What I can help you build: • AI agent systems using LangGraph, LangChain, MCP, A2A, FastAPI, and custom tool orchestration • RAG applications over documents, databases, knowledge bases, and enterprise data • Semantic layers and ontology-driven systems for analytics and GenAI use cases • Text-to-SQL / natural language database querying over Postgres, BigQuery, and Teradata • Knowledge graph RAG using Neo4j, vector databases, metadata extraction, and domain modeling • Full-stack AI SaaS products with Python, React, Next.js, Docker, Kubernetes, and cloud deployment • LLM fine-tuning, evaluation, prompt engineering, retrieval evaluation, and hallucination reduction Relevant achievements: • Led a 14-member team to build an asynchronous, extensible, A2A-compliant agentic framework for enterprise troubleshooting. • Reduced ticket resolution time in a production troubleshooting workflow from days to minutes. • Built and deployed hundreds of tools across multiple MCP servers. • Led a 12-member team to build a natural language query platform for enterprise databases. • Improved NLQ accuracy using domain modeling, metadata generation, and knowledge graph traversal. • Built an ontology-powered Knowledge Graph RAG platform over unstructured enterprise data. • Co-founded and scaled an AI video translation/dubbing product from $0 to $100k revenue in 6 months. • Built computer vision systems deployed across industrial locations in India and Europe. Tech stack: Python, FastAPI, LangChain, LangGraph, LlamaIndex, OpenAI, HuggingFace, PyTorch, PEFT/LoRA, React, Next.js, Postgres, BigQuery, Neo4j, Pinecone, Docker, Kubernetes, ArgoCD, GCP, AWS, PySpark, Airflow. I am best suited for clients who need more than a prototype. I can help you go from ambiguous AI idea → system design → implementation → deployment → evaluation → production hardening.

𝗜𝗻𝘀𝗽𝗶𝗿𝗲𝗱 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 & 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 | 𝗜𝗜𝗧 𝗚𝘂𝘄𝗮𝗵𝗮𝘁𝗶 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 | 𝟱 𝗬𝗲𝗮𝗿𝘀 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 ✅ IIT Guwahati Alumnus with 5 Years Enterprise & AI Experience (TCS, HCL Technologies) ✅ Expert in Advanced AI Pipelines, Agentic Workflows, and GraphRAG Architecture ✅ Skilled in Python, FastAPI, Node.js, NestJS, Next.js, and Cloud Infrastructure ✅ Available 30+ hrs/week | Dedicated, reliable, and highly responsive ✅ Goal: Build a 100% Job Success Record on Upwork through top-tier engineering 🔴 I may be new to the Upwork platform, but I bring half a decade of production-level engineering experience scaling systems for global tech giants. 🔴 Transitioning to full-time freelance AI development investing my full focus, speed, and enterprise standards into your project. 🔹 AI & LLM Skills AI Agents / Agentic Workflows: LangGraph, CrewAI, AutoGen, CrewAI Multi-Agent setups Advanced RAG: GraphRAG, LlamaIndex, Knowledge Graphs via Neo4j, Hybrid Vector Search Frontier Models: Claude 3.5 Sonnet/Opus, OpenAI GPT-4o, Gemini 1.5 Pro, Llama 3.2 Vision Edge AI & SLMs: Ollama, Llama 3.1/3.2, Phi-4 (Quantized deployment for cost optimization) Voice & Multimodal AI: OpenAI/Gemini Native Realtime WebSockets APIs (Low-latency audio) Observability & Vector DBs: LangSmith, Pinecone, Qdrant, Milvus, Chroma DB 🖥️ Backend Skills Python (FastAPI, Flask) | Node.js, Express.js, Nest.js Real-Time Data Streaming: Kafka, Redis Streams, WebSockets API Development: Secure RESTful APIs, gRPC, and GraphQL Databases: PostgreSQL, Supabase, MongoDB, Redis (Semantic Caching) DevOps & Cloud: Docker, AWS (EC2, Lambda, S3, Bedrock), Vercel 🌐 Frontend Skills React.js, Next.js 15 (App Router, Server Components) TypeScript, Redux Toolkit, Tailwind CSS Building highly responsive, secure, data-driven AI SaaS Dashboards 🛠️ Tools & Technologies ML libraries: Scikit-learn, Pandas, NumPy LLM Fine-tuning & Optimization: LoRA, PEFT, Hugging Face Hub Version Control & CI/CD: Git, GitHub Actions 🌟 Why Work With Me? I am building my freelance portfolio after 5 years in enterprise engineering. I deliver fast, communicate clearly, and charge fairly while I establish my Upwork presence. Every project gets my full attention. Warm regards, Aman

I help startups and executives ship production AI agent systems, multi-agent orchestration, RAG pipelines, and LLM automation with Claude Code, OpenClaw, Hermes, and n8n orchestration | 40+ projects | 100% Job Success. ✅ Top Rated Plus — Top 1% of AI Specialists & ML Engineers on Upwork ✅ Founder & CEO of TensorFold.ai | Lead AI Engineer at Origin Studios ✅ Published AI researcher (LLM reasoning & structured prompting) ✅ Working alongside senior engineers from NASA, Apple, Harvard & Warner Records WHAT I BUILD 🤖 OPENCLAW & CLAUDE AGENT EXTRACTION (12+ Projects) I build, optimise, and secure elite agentic environments. Most production setups bleed $100+/month because skills bloat tokens, secrets sit in markdown files, and memory drifts across sessions. I fix all three: - FRAMEWORK & MODELS**: Expert deployment of OpenClaw, NanoClaw, NemoClaw, and the Hermes Agent stack. - COST & TOKEN Optimisation: Hardened SKILL.md, compacted context windows, and vaulted credentials via OneCLI to slice monthly API costs by 40–70%. - OMNICHANNEL AGENT Routing: Seamlessly wiring autonomous agents across WhatsApp, Telegram, Discord, Slack, Signal, and iMessage. 📚 RAG & Knowledge Systems — multi-source RAG, hybrid search, knowledge graphs, document pipelines with Weaviate, Pinecone, Qdrant, FAISS, pgvector 🧠 LLM Engineering — GPT-4/5, Claude, Gemini, LLaMA, Mistral; fine-tuning with PEFT (LoRA, QLoRA), LLM evaluation, prompt optimisation, cost/latency tuning ⚙️ AI Automation & Backends — FastAPI production APIs (auth, streaming, logging), n8n and workflow automation, email/CRM/Slack integrations ☁️ Cloud & MLOps — GCP (Vertex AI, Cloud Run, BigQuery), Azure (AI Studio, Functions), Docker, CI/CD RECENT RESULTS 🎵 AI transformation for a major US record label — automated label management, A&R workflows, and executive communications end-to-end, turning a fully manual operation into an AI-first organisation. 🧑‍💼 Agentic AI "chief of staff" systems for two senior entertainment & investment executives — unified calendars, email, deal flow, and reporting into a single AI-powered command center running on autopilot. 🚗 End-to-end ETL + AI insights platform for the US automotive market — processing 6M+ records daily from 18,000 dealerships, taming extreme data noise and anomalies into decision-ready dashboards for dealership owners. 🚀 REVOPS 360 (idea → funded MVP) — built the entire GenAI layer for a B2B RevOps platform: lead-gen agents, campaign creators, pitch generators, and LinkedIn assistants with 20+ modular tools and LLM routing logic. Now entering VC phase. 🏆 Resume Matcher (NLP) — transformer-based candidate shortlisting that cut hiring time by 70%. HOW I WORK 1️⃣ Free scoping call → clear proposal with milestones and acceptance criteria 2️⃣ Sprint-based delivery with demos every cycle — you see progress, not promises 3️⃣ Production handoff: documentation, deployment, and post-launch support I respond within a few business hours (CET, overlap with US mornings), communicate in fluent English, and stick around after launch to improve what we ship. EXPERIENCE SNAPSHOT (5+ years) 🏢 Founder & CEO — TensorFold.ai (AI product & consulting company) 🤖 Lead AI Engineer — Origin Studios (agentic mesh systems & multi-agent orchestration for enterprise and entertainment clients) 🧠 ML Engineer — DFKI (German Research Center for Artificial Intelligence) 📊 Research Assistant — NYU Tandon School of Engineering (large-scale NLP on millions of Amazon products) 🌍 Generative AI Engineer — Eriko AI | ML Engineer — Ezy-AI | Consultant — Systems Limited 🏆 Top Rated Plus on Upwork since 2022 — 40+ projects, 100% client satisfaction 🎓 M.Sc. Computer Science (AI), RPTU Kaiserslautern-Landau, Germany 📄 Published researcher — LLM reasoning & structured prompting (large-scale experiments across multiple frontier models) Let's turn your AI idea into a working, revenue-driving product. 📬 Message me — I'll reply with a concrete plan, not a sales pitch.

Last project: a multi-agent system that handles end-to-end case evaluation for a legal client, replacing what used to be hours of manual review. That's the kind of problem I like — turning a messy, manual workflow into a reliable automated system. I'm a Senior AI Engineer (5+ years) specializing in RAG pipelines, multi-agent architectures, and production LLM systems — from whiteboard to AWS deployment. Recent work: Built a multi-agent legal AI system — a conversational intake agent that evaluates cases and recommends outcomes in real time Designed a RAG pipeline over a dense regulatory corpus, cutting document retrieval time by 60%+ Built an e-commerce shopping agent (Amazon/eBay) using LLM-based intent classification — replacing hardcoded category logic with a dynamic query mapper Shipped scalable AI APIs handling thousands of daily requests at sub-200ms latency What I bring beyond code: I scope projects like a product engineer first — defining what "done" actually means (POC vs. production-ready) before writing a line of code. That means clearer expectations, fewer pivots, and timelines that hold. Stack: Languages: Python, Node.js LLM frameworks: LangChain, LlamaIndex, OpenAI, Claude, HuggingFace, Ollama Vector DBs: Pinecone, Weaviate, ChromaDB, pgvector Agent frameworks: AutoGen, CrewAI, LangGraph Cloud & MLOps: AWS (SageMaker, Bedrock, Lambda, S3, EC2), Docker, FastAPI Databases: PostgreSQL, MongoDB, Redis Search: Elasticsearch, FAISS Bonus: I also work fluently across English, French, and Arabic — useful if your project involves multilingual content, MENA markets, or non-English document corpora. I work autonomously and communicate proactively — you'll know exactly where a project stands at every stage, with no surprises near a deadline. If you need an AI engineer who can own both technical architecture and product judgment — let's talk.

🏆 AWS Certified Generative AI Developer - Professional 🏆 AWS Certified Machine Learning – Specialty 🏆 AWS Certified Data Analytics – Specialty 🏆 Google Cloud Professional Machine Learning Engineer 🏆 Google Cloud Professional Cloud Architect I help businesses design, build, and deploy production-ready Generative AI applications powered by LLMs, AI Agents, RAG pipelines, Voice AI, and workflow automation. With 8+ years of experience in Machine Learning, NLP, Computer Vision, and Cloud AI, I specialize in transforming AI prototypes into scalable, enterprise-grade solutions running on AWS, GCP, and Kubernetes. What I Build ✅ AI Agents & Agentic Workflows * Single-Agent & Multi-Agent Systems * LangGraph Agent Development * MCP (Model Context Protocol) Integrations * Tool Calling & Function Calling Agents * Autonomous Research & Task Execution Agents * AI Workflow Automation ✅ RAG & Enterprise Search * Retrieval-Augmented Generation (RAG) * Enterprise Knowledge Assistants * Internal Documentation Chatbots * PDF, SharePoint, Confluence & Website Search * Hybrid Search (Vector + Keyword) * Agentic RAG Architectures ✅ Conversational AI & Voice AI * AI Chatbots * Customer Support Assistants * AI Voice Agents * Call Center Automation * Real-Time Speech-to-Speech Applications * Voice Ordering & Appointment Booking Systems GenAI Technologies 📍 LLMs OpenAI GPT-4o, GPT-5, Claude, Gemini, Llama, Mistral, Gemma, AWS Bedrock 📍 Agent Frameworks LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, LangSmith, LangFuse 📍 Vector Databases Pinecone, Qdrant, Weaviate, Milvus, ChromaDB, pgvector, Elasticsearch, Redis 📍 Voice AI Vapi, ElevenLabs, Deepgram, AssemblyAI, Whisper 📍 Prompt Engineering & Optimization DSPy, TextGrad, Structured Outputs, Guardrails 📍 LLM Deployment vLLM, Hugging Face TGI, TensorRT-LLM, Ray Serve, TorchServe Machine Learning & MLOps 📍 TensorFlow 📍 PyTorch 📍 Hugging Face 📍 Scikit-Learn 📍 Spark ML 📍 Forecasting & Predictive Analytics 📍 Computer Vision Solutions Cloud & Infrastructure AWS: Bedrock, SageMaker, Lambda, ECS, EKS, Textract, Comprehend, Rekognition, Transcribe, Polly, Forecast, Personalize Google Cloud: Vertex AI, Agent Builder, Gemini, Document AI, Dialogflow CX, GKE, Cloud Run, Cloud Functions Azure: Azure OpenAI, Azure ML Infrastructure: Kubernetes, Docker, CI/CD, GitHub Actions, Terraform Industries Served ✔ Retail & eCommerce ✔ Manufacturing ✔ Supply Chain & Logistics ✔ Automotive ✔ Healthcare ✔ Financial Services ✔ Customer Support Operations Whether you need an AI Agent, RAG chatbot, Voice AI solution, LLM-powered application, or a complete GenAI platform deployed on AWS/GCP, I can help take your idea from concept to production.