Azure AI Search Experts in Germany

• Designed and developed a multi-tenant SaaS platform enabling organizations to build their own knowledge bases and chat with brand-customized AI assistants (white-label approach with dynamic branding per organization).
• Implemented a scalable RAG architecture with a GPT-4o tool-use loop, hybrid semantic search, and strict tenant isolation at database and search index level.
• Built persistent, project-like chat sessions including a streaming API (SSE), multilingual support, and speech input/output (STT/TTS).
• Delivered the cloud infrastructure as Infrastructure-as-Code, fully automated per-customer CI/CD pipelines, and an onboarding process for new tenants.

Technologies used: Python, FastAPI, Pydantic (v2 noted), Next.js, React, TypeScript, Tailwind CSS, OpenAI / LLMs (GPT-4o), Azure AI Search, Cosmos DB, Azure Blob Storage, Azure Cognitive Services Speech, Azure App Service, Azure Container Registry, Retrieval-Augmented Generation (RAG), Server-Sent Events (SSE), Docker, Terraform, GitHub Actions, REST, OpenID Connect (OIDC), Multi-Tenancy

• Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
• End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
• Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
• Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
• Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
• Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
• Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles

• Lecturer for the GenAI Track at the Master School Institute of Technology
• Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category classification (4-layer hierarchical) including human-in-the-loop validation

• Designing and implementing an interactive evaluation system for top executives to rate core competencies such as goal orientation, team culture, and strategic alignment.
• Integrating control mechanisms to enforce feedback limits and store evaluations in a central system to ensure data integrity.
• Optimizing data processing for personnel development by automating the merging of various information sources for form letters.
• Implementing technical data preparation and analysis for the annual compensation comparison in the financial sector.
• Developing automated processes for data preparation in Excel using Power Query, ensuring data integrity and anonymization according to data protection requirements.
• Automating personnel cost analysis by developing a solution to process data from the Paisy system into an SAP-compatible Excel file.
• Creating test cases, user documentation, and test plans for all developed systems.
• Technologies: Power Query, MS Office 2016 (Word, Excel, PowerPoint), Paisy, SAP, VBA.

• Two-month modernization of the management UI for AI-powered cameras
• Rewrote a complex React application to Vue 3 with single file components
• Set up the core architecture of the Vue application and configured Vite, Pinia, Router, I18n, ESLint, and Prettier
• Custom integration of Leaflet to display detection zones on images
• Assisted with backend extension and authentication adjustments

Projects:

Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:

• Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
• Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
• Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
• Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
• Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
• Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management

Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:

• Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
• Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
• Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
• Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
• DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
• Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
• Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git

• Focused on exploring the intersection of Music and AI.

• Agile setup of a multimodal analysis platform for training materials (video, audio, documents) using Scrum
• Extraction of context-relevant content based on user profiles & competency dimensions
• Personalized delivery of learning content to boost sales performance
• Close coordination with sales teams & stakeholders to validate features
• Use of Gemini, Whisper, Python & JavaScript, deployment on AWS, Perl for scripting data imports
• Integration into existing tools & CRM systems for smooth adoption
• Technologies used: Python, OpenAI, DB tech like PostgreSQL, CI/CD for Airflow DAGs, FastAPI