Swagger Experts in Munich

• Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
• Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
• Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.

Oracle Project Management and Automation

As part of the project, the operation of an Oracle infrastructure was automated by developing and enhancing Puppet modules and migrating existing Bash scripts to a standardized configuration management solution.

The aim of the project was to standardize and automate administrative processes, improve the maintainability of the Oracle platform, and increase the efficiency and traceability of infrastructure management through the use of Infrastructure as Code.

• Analysis and migration of existing Bash shell scripts to a Puppet-based automation solution
• Development and enhancement of Puppet modules for Oracle environments
• Automation of installation, configuration and operational processes using Infrastructure as Code
• Standardization and optimization of configuration management for Oracle systems
• Creation and maintenance of technical and operational documentation
• Planning, coordination and professional support during project implementation
• Operation and automation of Oracle systems on x86-based Linux server platforms
• Testing and quality assurance of the developed Puppet modules
• Analysis and resolution of technical errors as part of the automation and migration
• Close coordination with specialist departments and infrastructure teams to implement automation requirements

Technologies used: Puppet 7/8, SLES 15, Oracle 19, Oracle Grid, SVN, Windows Server, Confluence, VS Code, Ruby, Bash, Pass

• 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).

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
• Development of feature store and data synchronization between environments
• Data science: evaluation of different forecasting models, including CatBoost, Contextual Gamma and Random Forest; implementation of training pipelines using Kubeflow on Vertex AI; scaling and development of an event-driven interface using Kafka as a forecasting service; evaluation of MLFlow for model tracking and model registry
• Implementation of REST API using KeyCloak OAuth2 and OpenID (JWT)
• Monitoring: implementation of dashboards with Grafana, Prometheus, Mimir, Streamlit and Loki to monitor prediction metrics, GCP and Snowflake costs for pipelines, and system metrics
• Development of Copilot Agent Skills

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

• 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

• Overall responsibility for the project lifecycle from scope definition to completion
• Close collaboration with platform teams, IT leaders, and external service providers
• Application of SAFe principles and structured sprint work
• Creation of a migration roadmap with clear milestones
• Monitoring of the lifecycle: onboarding, repository migration, replication of permissions, and system tests
• Visualization of the architecture with PlantUML and Gliffy as well as documentation in Confluence
• Regular status reports and running knowledge transfer sessions

• Development of dynamic web components for displaying KPIs, intelligent map applications, and operational process analysis tools
• Angular 18+
• Leaflet, MapLibre
• NestJS, JavaScript, HTML, CSS
• PostgreSQL, GraphQL, RabbitMQ
• Gitea, Jenkins, Docker

• Designed and built from scratch the automation framework using Playwright, Typescript, JavaScript, Gherkin, Cucumber, BDD, Maven, IntelliJ IDEA
• Defined, developed and maintained test plans, test scripts, reports and other QA documentation in Confluence
• Created and maintained test data with SQL Server Management Studio, Toad and Faker.js
• Performed web services and API testing using Swagger Open API, SoapUI, JSON, HTML and XML
• Executed functional, smoke, regression, black box, GUI, cross-browser, UAT and E2E testing using CrossBrowserTesting and Safari Web Inspector
• Integrated and maintained automated scripts within sprints following Kanban, CI/CD, GitHub, Docker, Azure Pipelines, Agile, Scrum, Kafka and Kibana
• Raised and managed defects in Azure DevOps
• Conducted mobile testing with Robot Framework and Appium

• Test concept creation
• Creation of test processes
• Coordination of TC development: stress tests, functional tests, performance tests, high data rate tests, integration tests, etc.
• HW testing: FPGA, RF
• Test automation and regression tests
• Ensuring 24/7 operation of the test system
• Analysis & reporting
• Regular coordination of the test team, meetings with other stakeholders
• Communication and coordination with stakeholders and the project manager

• Participated in the Riyadh Public Transport (KAPT) project introducing public transportation in Riyadh, supporting multimodal journeys combining bus, metro, car on demand.
• Worked via Thiqah and partnered with Andersen to refactor the mobile MaaS application DARB into a new microservices architecture under SCRUM framework, successfully completing Phase 1.
• Facilitated a team of 40 developers across Android, iOS, Web, Java, DevOps, architecture, analysis, and QA.
• Moderated Scrum events and communicated with the client, proactively reporting on project deadlines, scope, and challenges.
• Coordinated cross-team efforts between Thiqah specialists and GPS development teams, managing Jira and Azure DevOps trackers.
• Supported and improved Scrum processes throughout the project.
• Due to Thiqah’s takeover by Elm, subsequent phases were handled entirely in Saudi Arabia with GPS providing IT consulting.
• Tools: Azure DevOps, Jira, Confluence, Draw.IO, ChatGPT

• Set up the go-to-market for Metyis DE by defining productized offerings that enabled onboarding of 5+ enterprise clients
• Successfully ran client projects, like ramping up the global marketplace business at a European consumer electronics company and scaling the DACH operations of two Dutch e-commerce and a German B2B nutrition business

• Backend development of B2B e-commerce solution using SAP Commerce Cloud, leveraging Java and Spring Framework with creation of REST APIs for effective communication.
• Resolved software defects, developed automated cron jobs and triggers, and authored unit tests with JUnit to uphold code stability and quality standards.
• Utilized Git-based version control systems (Bitbucket/GitHub) for source code management and used Jenkins to support continuous integration and development (CI/CD).
• Executed and closed multiple user stories and tickets across iterative bi-weekly sprints under Agile (SCRUM) methodology.
• Led incident resolution in the production environment and minimized downtime through real-time monitoring (Solr, SAP CCv2, OpenSearch Dashboards) and sustaining SLA targets above 99%.