Angular Experts in Munich

• AI Integration (LLM & RAG): Designed and built an internal intelligent RAG system (Retrieval-Augmented Generation) based on LLMs, n8n, and vector data to automatically analyze technical documents and error logs.
• Design & Implementation: Designed a robust RS-232/UART communication interface for an SBC-based embedded device used to control medical shaker systems.
• Architecture & Protocol Design: Built a highly maintainable software structure (OOP, SOLID) and defined resilient, hardware-level communication protocols, including multithreading and advanced error handling.
• Quality Assurance & DevOps: Automated testing with xUnit, ran integration tests directly on the hardware target, and maintained technical documentation to strict medical technology standards via Azure DevOps.

Label: C#, .NET, LLMs, RAG, n8n, RS-232, UART, Multithreading, async/await, xUnit, gRPC/protobuf, Blazor, MudBlazor, EF Core, Visual Studio 2026, Azure DevOps

Topics:

• Further development of the CRM system NKAM and technical separation of “direct” and “indirect” sales
• Redesign of the discount management area and outsourcing to another system.
• Designing numerous improvements on the wholesale side to reduce manual effort down to the level of user stories.

• Designing AI-first workflows that integrate AI into existing product experiences
• Developing UX concepts for prompt management, reusable and combined prompt workflows, tagging, search and information organisation
• Creating user flows, wireframes, prototypes and high-fidelity interfaces in Figma
• Defining reusable UI patterns, components and interaction logic for scalable products
• Exploring human-AI interaction patterns with emphasis on user control, transparency and manageable cognitive load
• Translating product requirements and technical constraints into developer-ready UX/UI specifications

July 2024 - June 2025

• Accessibility expert in the field of UI/UX design, WCAG testing, and consulting for the Accessibility Strengthening Act
• Creation of an internal accessibility guide

Oskar Oldorf (project lead): "I had the pleasure of working with Patricia for over a year on a project focused on ensuring digital accessibility for the online presence of a company in the financial services sector. During that time, I got to know her as a dedicated, detail-oriented, and highly skilled colleague.

Patricia was responsible for independently conducting gap analyses and worked directly and efficiently with key stakeholders. Her role centered on assessing compliance with the BFSG and providing strategic guidance to editorial teams on creating accessible content.

What I particularly appreciated about Patricia was her ability to think beyond the status quo and bring fresh perspectives to the table. She combines strong subject matter expertise with a keen eye for detail and a structured, thorough approach. Her input often sparked valuable discussions and helped us move our work forward in meaningful ways.

I can wholeheartedly recommend Patricia—especially for roles where precision, strategic thinking, and a high standard of quality are essential."

• Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
• Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
• Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
• Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
• Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
• Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
• Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
• Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
• Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
• Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
• Integration of RESTHeart to create a REST API for MongoDB.
• Build an Angular frontend to simplify data queries and master data maintenance.
• Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
• Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).

struppilog.com – Digital health record for pets / MVP → Full Product

Design, development, and full further development of a digital health platform for pets – from my own MVP development to a fully built and production-ready platform.

Independent concept and development of the MVP Development of the full application with Flutter/Dart and Firebase Expansion of the MVP into a full digital health record with health data, findings, allergies, medications, documents, and emergency data Development of user registration, authentication, roles, data models, and secure user interactions Implementation of QR-code-based data exchange and digital interaction features Development of a multilingual, responsive web application Integration of AI-supported features and AI/agentic workflows Development and continuous improvement of product logic, UX/UI, and technical architecture Building and expanding a scalable cloud-based solution with Firebase Integration and further development of APIs and external services Use of AI-native / agentic engineering to speed up development, testing, debugging, and product iteration Independent implementation of all other features and technical extensions Continuous further development of the MVP into a full digital product

Impact: The MVP I built myself was continuously developed technically and functionally into a broad, production-ready platform – including frontend, backend, data model, authentication, UX/UI, APIs, cloud infrastructure, and ongoing product development.

BMW AG · Mercedes-Benz AG · Munich Re · CARIAD / VW Group

• Leading UX and product direction of PromptM, an enterprise AI prompt management platform at BMW, designing human-agent interaction models, role-based governance flows, and a Playground testing environment for prompt validation and iteration
• Redesigned insurance policy workflows at Munich Re, restructuring form layouts, improving field prioritisation based on user needs, and introducing new design components into the existing product system
• Led end-to-end UX at BMW shopfloor: user flows, wireframes, usability testing, and Figma design system adopted across 5+ agile squads, reducing order processing time by 35%
• UX Coach at Mercedes-Benz, upskilling 50+ team members in user research, usability testing, and agile UX methods; reduced design-to-dev handoff by 30%
• Facilitated 10+ design sprints and discovery workshops; enforced WCAG 2.1 AA accessibility across all deliverables

Tasks

• Further development of a new ERP system with Blazor
• Generation of e-invoices in the XRechnung and Zugferd formats
• UI/UX design Client-server system
• Windows 11 Technology
• Microsoft .NET 9, Git, Azure DevOps, ASP.NET, MSSQL, Blazor Programming languages
• C#, MVVM Development tools
• Microsoft Visual Studio .NET 2022 Database
• MSSQL Industry
• Other

Conducted an independent technical assessment of an AI-enabled software platform, combining AI risk auditing, cybersecurity analysis and software architecture review. Reviewed application components, APIs, data flows, LLM integrations, retrieval-augmented generation, multi-agent orchestration, authentication, tenant isolation, dependency vulnerabilities, AI governance and model lifecycle controls. Authored a technical audit report with a structured risk register, source-code evidence, regulatory references, corrective actions, AI system inventory, risk classification, remediation roadmap and Key Risk Indicators.

Technologies: TypeScript, JavaScript, React, Next.js, Node.js, REST APIs, MongoDB, Redis, AWS serverless services, OAuth 2.0 / OpenID Connect, LLM APIs, RAG, vector search, multi-agent orchestration, Model Context Protocol, C4 architecture modelling, threat modelling, NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894, OWASP guidance, MITRE ATLAS

• Spring Boot Software Engineer
• DevOps Engineer (Kubernetes, Azure DevOps)

Toolstack: Java, Spring Boot, Kubernetes, Helm, GitOps, ArgoCD, Docker, Azure DevOps, CI/CD Pipelines, Git, Postgres

• Development of the digital organ donation register, commissioned by the Federal Institute for Drugs and Medical Devices (BfArM)

• Implementation of user stories in several microservices (frontend and backend)

• Ensuring quality with unit, integration, and E2E tests

• Conducting code reviews

• Coordination with other development teams

• Taking over the software license check and simplifying the process

• Responsibility for implementing and documenting the business logging

• Setting up a development environment with Docker Compose

• Analysis of affected business processes taking numerous stakeholders into account
• Interface analysis, architecture and system design
• Communicating and coordinating various subprojects and interface partners
• Creating epics and user stories, maintaining the backlog, workshops and review presentations
• Support during implementation between business departments and development
• Test management including strategy and approach definition
• Test case definition, execution and approval
• Cross-team organization of integration and acceptance tests
• Support of test environments
• Technologies and tools: Java, Angular, Kubectl, REST, AWS SNS/SQS, Kafka, S4/HANA, Bruno

• Mentoring startups about technology trends and solutions, business models, market and competition research.

Functional design and specification of key SAP GTS processes, including

• Compliance,
• EU Preference Management and
• Reporting. Translate business requirements into specifications ready for implementation by third-party development teams.