Rafidul Rafid
Engineer
Overview
AI/MLOps Engineer with hands-on experience building and deploying production AI systems on Microsoft Azure; including LLM-powered RAG chatbots, agentic AI workflows, and multimodal OCR microservices. Experienced in end-to-end Azure deployment, CI/CD pipelines, containerisation (Docker/Kubernetes), and secure access management. Proven track record: 99% accuracy on a live RAG chatbot and 98% OCR accuracy on HIPAA-compliant medical document pipelines. Bridging AI engineering and cloud platform roles.
AI/MLOps Engineer · Azure · Cloud Infrastructure · Secure AI Deployment
Specializing in Machine Learning, NLP, Computer Vision, and Scalable Software Development.
- Birthday: 16 November 1998
- Address: Germany
- Company Email: rafidul.rafid@baywa-re.com
- Phone: +49 1575 3255 867
- Degree: B.Sc. Artificial Intelligence
- Email: rafid.4507@gmail.com
- Available: From January 2027
Core focus: Azure Cloud (AKS, App Services, Key Vault, Entra ID) · AWS · DevOps & CI/CD · LLM Agents & RAG · MLOps · Infrastructure as Code · Secure AI Deployment
Years of experience
Projects
Current role
Available from
Skills
Cloud-native AI engineering — deploying secure, scalable LLM solutions on Azure, AWS with DevOps best practices
Programming
Microsoft Azure
DevOps & IaC
Enterprise Identity & Security
LLM Systems & Agentic AI
ML / Deep Learning
NLP & Computer Vision
Languages
Working proficiency in German and English
Resume
AI/MLOps Engineer with strong foundation in cloud infrastructure, secure AI deployment, and production ML systems.
Summary
Rafidul Rafid
AI/MLOps Engineer with production experience building and deploying AI platforms on Microsoft Azure. Built end-to-end architectures: LLM agents, RAG chatbots (99% accuracy), HIPAA-compliant OCR pipelines (98% accuracy), and secure CI/CD deployments on AKS and App Services. Currently IT Administrator at BayWa r.e. (Munich), formerly Junior AI/ML Engineer at Nubedian GmbH (Karlsruhe).
- AI/ML Engineer
- Deployed scalable AI infrastructure on Azure serving hospital production systems
- Expected graduation date: January 2027
Education
B.Sc. Computer Science & Artificial Intelligence
October 2022 – January 2027 (Expected)
Technische Hochschule Ingolstadt, Germany
- Machine Learning, Deep Learning, NLP, Computer Vision, Cloud Computing, Software Engineering
- Grade: 2.6
B.Sc. Statistics
January 2019 – March 2021
Shahjalal University of Science and Technology, Bangladesh
- Linear Algebra, Probability Theory, Real Analysis, R Programming, Data Visualization
- Grade: 1.7 / 1.0
Bachelor Thesis (Grade 1.3)
Nubedian GmbH, Karlsruhe, Germany
"A Hybrid Multi-Layer Framework for Secure Medical Document Parser"
Developed a multi-layer engineering framework using LangChain and LangGraph to automate context-aware routing and data extraction from unstructured medical files. Engineered a secure text-processing pipeline using OpenCV and Tesseract. Containerized the application with Docker and established automated deployment pipelines to scale the microservices.
Volunteer Work
Research Coordinator — AI/ML Research Opportunities
March 2023 – December 2023
Open Researcher's Space | Technische Hochschule Ingolstadt, Germany
- Reviewed AI/ML research papers with faculty across multiple universities; organized interdisciplinary AI workshops and seminars.
Professional Experience
IT Administrator
April 2026 – Present
BayWa r.e., Munich, Germany
Device & Access Management
- Administer enterprise identity lifecycle and access controls (RBAC) via Microsoft Entra ID, ensuring secure authentication and least-privilege compliance across corporate environments.
- Provision, configure, and maintain hardware endpoints (Windows, macOS, iOS) via Microsoft Intune, enforcing compliance policies and automated security baselines.
- Deliver diagnostics, device provisioning, and system maintenance across enterprise workstations, minimizing downtime for on-site and remote teams.
- Standardize technical incident resolution paths and draft automated PowerShell routines/documentation to streamline repetitive support handovers and operational workflows.
Junior AI/ML Engineer
October 2024 – February 2026
Nubedian GmbH, Karlsruhe, Germany
Healthcare AI & Azure Cloud Deployment
- Architected and deployed production RAG pipelines (LangChain, FAISS) achieving 99% accuracy on hospital patient queries; fine-tuned open-source LLMs and built multi-agent orchestration workflows utilizing Model Context Protocol (MCP) and self-hosted n8n.
- Governed end-to-end cloud security and compliance lifecycles on Azure; implemented cost tracking and compute provisioning alerts to optimize cloud expenditure across production AI workloads.
- Containerized (Docker) and deployed production AI microservices on Azure App Services and REST APIs integrated into hospital management workflows, managing secrets with Azure Key Vault and access via Managed Identities.
- Engineered an end-to-end OCR and document digitization microservice (EasyOCR, Tesseract, OpenCV, LLM post-processing) achieving 98% accuracy, embedding automated PII redaction to enforce zero-trust clinical data privacy.
- Automated continuous deployment workflows for LangChain-based services, implementing health checks, compute scaling, and resource monitoring to ensure high availability across environments.
- Monitored Azure resource consumption and pipeline health; implemented usage alerts and optimised compute provisioning to maintain cost efficiency across AI workloads.
Software Engineer
February 2024 – October 2024
Schanzer Racing Electric e.V., Ingolstadt, Germany
Embedded Systems
- Developed backend services using Django and Node.js to ingest, process, and stream real-time vehicle sensor data to the pit crew dashboard.
- Optimised aerodynamic models in MATLAB/Simulink to enhance vehicle dynamics.
- Managed version control via Git/Bitbucket within a cross-functional team to maintain high-velocity software releases.
Projects
Production AI systems and cloud-native tools — from Azure-hosted LLM agents and RAG chatbots to OCR pipelines and financial models.
- All
- AI / ML
- Cloud / DevOps
- Certification
MRI Diffusion Distortion Correction CNN (PyTorch)
June 2024
Technische Hochschule Ingolstadt (Supervisor: Prof. Dr. Marion Menzel) · CNN · PyTorch · Medical Imaging · Built a CNN model for geometric distortion correction in MRI diffusion images, including custom data preprocessing and augmentation pipelines.
Testimonials
What colleagues and professors say about my work
Contact
Feel free to reach me via email or phone.
Address
Germany
Call Me
+49 1575 3255 867
Email Me
rafid.4507@gmail.com