Rauhan
Ahmed
Designing & shipping autonomous AI agents, enterprise RAG, and production Machine Learning systems.
- Sutra.AIEnterprise AI & Agents
- Revive AnalyticsColorado, USA
- Saffire TradewingsQuantitative ML
- Tech Consulting PartnersLondon, UK
- Ineuron IntelligenceBangalore, India
- Rocket Capital AI1st Place Winner (5,000+ competitors)
- Citi Bank HackathonTop 10 National Finalist
- Accenture AI HackathonTop 8 Finalist
- Stanford UniversityMachine Learning
- IBMDeep Learning with PyTorch
Senior AI Engineer bridging deep research models and resilient production systems.
Rauhan Ahmed Siddiqui — Senior AI Engineer with 5+ years of experience architecting end-to-end AI systems, autonomous multi-agent pipelines, and enterprise data platforms.
Enterprise Multi-Agent Architecture
Architected 8+ multi-agent platforms serving 15,000+ users across manufacturing, logistics, and analytics with autonomous browser validation and tool orchestration.
Contextual RAG & Knowledge Retrieval
Engineered production RAG pipelines integrating enterprise document stores, live SQL databases, and vector stores (Qdrant, Pinecone), boosting query resolution speed by 65%.
Multimodal & Vision-Language Intelligence
Built automated visual damage inspection models with high-precision before/after comparisons and GAN-based restoration pipelines.
Cloud Infrastructure & High-Throughput MLOps
Deployed 25+ containerized FastAPI microservices on AWS Bedrock and GCP Vertex AI with CI/CD automation, ensuring 99.9% uptime at scale.
Hackathons & Industry Honors
- Winner, Global AI Crypto Forecasting Competition1st Place (5,000+ Competitors)
Secured 1st place among 5,000+ global data science participants in quantitative time-series forecasting.
Rocket Capital - Top 10 Finalist & Cash PrizeTop 10 Finalist & Prize Winner
Awarded Amazon Alexa and cash prize for innovative AI financial automation solution.
Citi Bank Hackathon - Top 8 FinalistTop 8 Finalist
Engineered high-impact enterprise AI workflow solution judged among top 8 national finalists.
Accenture AI Hackathon - 1st Place, Inter-College Coding Hackathon1st Place (800+ Participants)
Ranked 1st among 800+ student and professional software engineers.
Inter-College Hackathon
Academic & Professional Credentials
Formal Education
Comprehensive curriculum focused on Machine Learning, Distributed Systems, Data Structures & Algorithms, and Cloud Computing.
Professional Certifications
- Machine Learning SpecializationStanford University (DeepLearning.AI)
- Deep Learning with PyTorchIBM
- Python for Data ScienceIBM
Four architectural domains built for enterprise reliability.
From multi-agent graph topologies to high-throughput cloud microservices with sub-second inference.
- 01
Multi-Agent Systems & Autonomous Workflows
Autonomous agent architectures orchestrating complex tools, browser automation, document intelligence, and multi-agent coordination with LangGraph, CrewAI, FastMCP, and Google ADK.
Architectural Highlights- Multi-agent graph topologies for hierarchical decision-making and cross-tool orchestration.
- Browser-controlled AI agents for automated visual web validation and data extraction.
- Model Context Protocol (MCP / FastMCP) servers connecting enterprise tools directly to LLM runtimes.
- LangGraph
- CrewAI
- MCP / FastMCP
- Google ADK
- Python
- FastAPI
80% reduction in manual review effort · 8+ enterprise platforms deployed
- 02
Enterprise RAG & Context-Aware Search
Production-scale RAG systems integrating proprietary enterprise documents, live SQL databases, catalog systems, hybrid vector search (Qdrant, Pinecone), and multimodal retrieval.
Architectural Highlights- Hybrid semantic + dense keyword search with contextual rerankers and metadata filtering.
- Live SQL schema routing allowing natural language querying over relational enterprise data.
- Context compression and chunking strategies tailored to technical and legal documentation.
- LangChain
- Qdrant
- Pinecone
- OpenAI
- Gemini 2.5
- Anthropic Claude
65% faster operational queries · +25% contextual relevance
- 03
Vision-Language & Generative AI
Vision-Language Model inspection systems for automated asset & vehicle damage analysis, high-accuracy before/after comparisons, image upscaling (GANs), and diffusion models.
Architectural Highlights- Automated visual damage inspection with sub-millimeter anomaly detection workflows.
- Fine-tuned generative diffusion and GAN pipelines for background and facial restoration (HyperRez).
- Virtual try-on systems combining CLIP embeddings with conditional image generators.
- Vision-Language Models
- PyTorch
- OpenCV
- Diffusers
- RealESRGAN
- CLIP
45% increase in inspection reliability · 7K+ package downloads
- 04
MLOps, Cloud & High-Throughput APIs
Scalable, containerized AI microservices on AWS (Bedrock, Lambda, ECR, EC2) and GCP (Vertex AI, RAG Engine) with automated CI/CD, MLflow tracking, and Docker Compose.
Architectural Highlights- Containerized FastAPI microservices with Celery task queues, Redis caching, and Pydantic validation.
- Automated CI/CD pipelines via GitHub Actions with regression testing and semantic model versioning.
- Cloud cost optimization through selective LoRA adapter routing and quantized inference.
- AWS Bedrock
- GCP Vertex AI
- FastAPI
- Docker Compose
- MLflow
- GitHub Actions
99.9% uptime · 40% reduction in deployment time
Production-tested across research, distributed agents & cloud infrastructure.
Programming & Core
AI, ML & Generative AI
Data & Databases
APIs & Application Dev
MLOps & Automation
Cloud Platforms
Engineering leadership across enterprise platforms, agentic AI & production ML.
- Dec 2025 – PresentCurrent
- Architected and deployed 8+ enterprise-grade AI platforms and multi-agent systems across manufacturing, logistics, and analytics domains, collectively serving 15,000+ users and processing 100K+ monthly AI interactions.
- Built production-scale RAG and agentic AI applications integrating proprietary enterprise documents, live SQL databases, catalog systems, internet search, and multimodal retrieval pipelines, improving operational query resolution speed by 65%.
- Engineered autonomous evaluation and workflow automation systems using browser-controlled AI agents, video understanding, document intelligence, and internet validation pipelines, reducing manual review effort by 80%.
- Developed Vision-Language Model based inspection systems for automated asset and vehicle damage analysis with high-accuracy before/after comparison workflows, improving inspection reliability by 45%.
- Implemented scalable AI infrastructure using FastAPI, AWS Bedrock, Google Vertex AI, MCP integrations, Docker Compose, and distributed agent architectures, enabling reliable high-throughput enterprise deployments with 99.9% uptime.
- Oct 2024 – Dec 2025
- Architected and delivered an end-to-end GenAI analytics platform integrating LLM-based components and agentic workflows, improving insight generation speed by 70%.
- Built production-ready FastAPI microservices for AI pipelines, reducing model deployment time by 40%.
- Designed RAG workflows using advanced search methods and Qdrant Vector DB for context-aware retrieval, boosting response relevance by 25%.
- Implemented fine-tuning and LoRA-based adaptation for open LLMs, improving factual consistency and latency.
- Collaborated with data and product teams to ensure reproducibility, clean experiment tracking, and cloud scalability.
- Mentored 3 interns on model evaluation and prompt optimization best practices, accelerating internal prototyping cycles.
- Apr 2023 – Sep 2024
- Designed forecasting systems for NIFTY50 portfolios using LSTM and XGBoost, achieving 52% improvement in accuracy.
- Developed ML-powered financial signal detection and anomaly monitoring pipelines handling 300+ data streams in real-time.
- Architected a CNN-LSTM ensemble for time-series classification, reducing portfolio drawdown by 70%.
- Built ML dashboards with Streamlit for financial performance visualization and model explainability.
- Optimized feature engineering and model versioning workflows to cut training costs by 30%.
- Feb 2022 – Apr 2023
- Developed an enterprise-grade chatbot using LangChain and Hugging Face for contextual document retrieval (RAG-based).
- Deployed over 25 FastAPI-based ML microservices integrated with CI/CD pipelines across cloud platforms.
- Built a virtual try-on GenAI system combining CLIP and diffusion models, enhancing customer engagement by 30%.
- Collaborated with design, data, and backend teams to automate model inference, validation, and monitoring workflows.
- Dec 2020 – Feb 2022
- Built ML models using CatBoost and RandomForest for financial risk prediction, achieving 84%+ production accuracy.
- Performed feature engineering, hyperparameter tuning, and data cleansing to improve model interpretability.
- Developed Flask APIs for real-time inference and implemented retraining scripts for continuous model updates.
- Collaborated with analysts to translate model outcomes into actionable business recommendations.
- Mar 2022 – Dec 2022
- Mentored 10+ students in applied ML, predictive analytics, and project-based learning.
- Designed modular course content emphasizing reproducibility and deployment of ML models.
- Acted as primary technical reviewer for student projects, improving project completion quality by 25%.
Production AI agents, open-source libraries & technical research.
From autonomous multi-agent financial intelligence to computer vision libraries with thousands of global downloads.
Stock Analysis Dashboard & Financial Analyst Agent
Autonomous financial intelligence platform acting as a multi-modal investment analyst.
Sole architect of an autonomous AI agent system leveraging Google Gemini 2.5 and Agno to ingest live market feeds, execute natural language queries, and generate investment dossiers via interactive Streamlit visualization.
ConversAI: Conversational AI Agent Framework
End-to-end conversational agent framework with multi-source ingestion and autonomous workflows.
Engineered an extensible conversational AI agent managing full user workflows from multi-source extraction (PDFs, YouTube videos, web URLs) to semantic reasoning and automated action dispatch.
HyperRez: GAN-Powered Image Upscaling Library
Published open-source library delivering state-of-the-art super-resolution in 3 lines of code.
Engineered a lightweight Python library combining RealESRGAN for background super-resolution and GFPGAN for facial feature reconstruction with 7,000+ all-time global developer downloads.
Conversational Data Analyzer
Natural language tabular data analytics powered by Groq ultra-fast inference and Mixtral 8x7B.
Built a conversational intelligence application enabling non-technical stakeholders to upload complex CSV/SQL datasets and receive instant code execution, exploratory charts, and automated trend summaries.
Transformers: The Engine Powering ChatGPT and Beyond
Comprehensive architectural breakdown of self-attention mechanisms and generative LLMs.
Authored an in-depth technical analysis covering scaled dot-product attention, multi-head projections, positional encodings, and scaling laws governing frontier language models.
Llama 3.2 3B Reasoning via DeepSeek-R1 GRPO
Post-training reasoning adaptation using Group Relative Policy Optimization (GRPO) to elicit autonomous chain-of-thought deliberation in compact language models.
Engineered a reinforcement learning pipeline implementing DeepSeek-R1's GRPO framework on Llama 3.2 3B, training the model to self-generate structured <think> reasoning tokens and achieve elevated mathematical problem-solving accuracy on GSM8K.
GemFit: AI Virtual Jewelry & Fashion Try-On Solution
AI-powered virtual try-on solution leveraging Stable Diffusion inpainting and real-time computer vision tracking for photorealistic jewelry and apparel fitting.
Engineered an open-source virtual try-on pipeline combining Stability AI Stable Diffusion 2 inpainting with MediaPipe facial and hand keypoint tracking, OpenCV spatial alignment, Appwrite secure storage, and xFormers memory optimization for seamless real-time jewelry and clothing placement.
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Open to discussing senior AI, Machine Learning, and Data Science systems architecture — consulting, advisory, or high-impact engineering engagements.