GitHub Actions Experts in Germany

• Developed browser based platform for kubernetes no-code deployment and cluster management
• Developed CLI in Typescript to deploy the resources in the cluster without leaving the browser UI.
• Implemented DevSecOps pipelines: image scanning, SBOM, policy enforcement, supply-chain security and used Kyverno. Implemented IAM integration for the command line utility tool.
• Designed role & permission models for Keycloak, oAuth/OIDC, social login flows.
• Used LLM to convert user intent into the diagram.
• Worked on integration with multiple Sovereign Cloud like stackIt, Hetzner, CIVO, UpCloud plus public clouds like AWS, GCP, Azure
• The technology stack includes Java, SpringBoot, Kubernetes, OpenAI, Kubernetes multi-tenancy using vCluster, Karpenter, RBAC for CLI, Helm, React

TOURISM

colle-il-diaccino.de · Holiday Accommodation

• Designed and developed the website: interactive site map, accommodation comparison, and image galleries.
• Implemented German, English, and Italian language versions. Set up inquiry forms with input validation and spam protection, language-specific SEO metadata, and automated tests.

Stack: Next.js, React, TypeScript, Tailwind, next-intl, React Hook Form, Zod, Resend, Playwright, Vitest

• Create and lead roadmap forecasting of support opportunities, including colleague training, process design and improvement, and new hire onboarding.
• Collaborate seamlessly with cross-functional teams including Professional Services, Support, Product, Sales, and Solution Engineering.
• Manage business and financial KPIs in alignment with overall business objectives.
• Industrial IT & Data Integration: Implement, configure, and integrate OT/IT systems and data flows, connecting control-layer sources (DCS, PLC, SCADA) to historians, data platforms, and enterprise systems through APIs and standard interfaces.
• AVEVA PI & Historian: Configure, maintain, and extend AVEVA PI (PI Data Archive, Asset Framework, interfaces/connectors) to capture, contextualize, and serve real-time and historical operational data.
• Alarm Management: Support and optimize alarm management systems – e.g. Honeywell Alarm Management – including alarm rationalization, classification, and the analysis of alarm performance, critical alarms, and alarm floods.
• Connectivity & Protocols: Set up and troubleshoot industrial connectivity using OPC UA and OPC A&E, including the configuration of tunnelers / wrappers to bridge OT data sources securely and reliably.
• Production Data Flow: Ensure seamless, secure, and well-structured data flow across the industrial IT landscape, transforming raw operational data into meaningful information for operations and decision-making.
• System Support & Troubleshooting: Provide ongoing support for OT/IT applications, troubleshooting issues across networks, software, and data integrations to keep systems running efficiently.
• Knowledge Management & Best Practices: Contribute to internal documentation, best practices, and troubleshooting guides, and help continuously improve how we deliver industrial IT and data solutions.

Tools & Software: Aveva PI, Salesforce, Active Directory, Microsoft Dynamics 365, Jira, Microsoft, Scrum, DevOps, Docker, CI/CD, Jenkins, GitHub.

Product:

• Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
• Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
• Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
• Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
• Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

• Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
• Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.

• Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility

• Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture

• Pipeline orchestration with Azure Data Factory

• Improved and automated the development and deployment process by integrating Git and GitHub Actions

• Technical leadership of the Data Engineering team (3 employees)

• Led workshops to optimize and stabilize the data platform and development process

• Collected and prioritized new requests and maintained the product backlog

• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural

• Development of scalable backend applications with C#/.NET and Java
• Design and implementation of distributed microservice architectures
• Development and integration of REST APIs for industrial applications
• Development of modern web applications with React, Angular, and TypeScript
• Implementation of MQTT-based communication solutions
• Integration of industrial protocols such as OPC UA and Modbus TCP
• Development of batch, process control, and HMI components
• Containerization and deployment of applications with Docker
• Conducting code reviews and supporting architecture decisions
• Close collaboration with Product Owners, QA, and interdisciplinary teams
• Analysis of business requirements and implementation of technical solutions
• Further development of existing software architectures with a focus on maintainability and performance

Technologies: C#, .NET, ASP.NET Core, Java, C++, React, Angular, TypeScript, Vue.JS, MQTT, OPC UA, Modbus TCP, Docker, GitLab, MariaDB, MySQL, Linux

• Claude Code subagents, MCP, Pydantic V2, pytest, bandit

• Designed and shipped 3 specialized agents that hand work down a line: a research agent writes a cited implementation spec, a coding agent builds the modular code and its tests, a review agent ranks findings by severity and applies the fixes. Each handoff is a structured document, so no stage depends on another agent's context window.

• Connected the research agent to an academic-research MCP server (Semantic Scholar, ArXiv, Hugging Face Hub, citation snowballing) so every reference traces to a tool result rather than the model. Gated commits behind ruff, mypy, pytest and bandit, required human sign-off before installs and commits, and persisted session state on disk so long runs survive a context reset.

Project: Defect Generation on Test-Bench Images of Metal Surfaces Environment: Automated Visual Inspection (AVI), Metallurgy & Manufacturing

• Objective & Implementation: Designed, architected, and trained Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g., cracks, inclusions, scale) on rough metal surfaces under real test-bench lighting conditions for privacy-compliant and efficient dataset expansion (data augmentation).
• Technical Design: Implemented robust Generative AI and computer vision pipelines in Python and PyTorch. Used semantic segmentation approaches for mask-controlled defect synthesis and subsequent evaluation with EfficientDet object detection models.
• Business Impact: Massive dataset upscaling (10x) without time-consuming and costly physical test-bench runs, while significantly improving the detection performance of automated inspection systems.

Technologies & Skills Used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision

Maturing their API practices on both a business and technology level. My role covers strategy, architecture, developer advocacy as well as hands-on software engineering, enabling both technical teams and business leadership to adopt and act on API-centric principles effectively. Coincidentally, we also establish GitOps, DX and platform best practices with this project.

Highlights:

• Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
• Formulating a way forward for API Lifecycle Management at OTTO
• Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals

API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, React, Node.js, TypeScript, Redocly, reactive programming, CDC, Golang, Gin, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.

• Focus: System architecture, cloud-native platforms, microservices, API design
• Product: Pflege-Pfad is a digital placement platform that directly connects relatives of people in need of care with verified care services and caregivers – without an agency and without ongoing fees.
• Business analysis & process design:
• Analysis of the German care market and identification of the key pain points of both target groups.
• Modeling of core business processes: registration, verification, care request, application, placement, and rating.
• Definition of the business model as a freemium/premium model with optional contact unlocking.
• Creation of user stories and requirements documentation for relatives, care services, and administrators.
• Design of trust and quality assurance mechanisms with document upload, admin review process, and rating system.
• Coordination with stakeholders and validation of product decisions with potential users.
• Technical implementation:
• Design and implementation of the entire platform architecture as the sole developer.
• Design and implementation of a REST API with Spring Boot and Kotlin, including JWT-based authentication.
• Development of the frontend as a single-page application with Angular 17.
• Implementation of the AWS infrastructure with EC2, RDS PostgreSQL, S3, CloudFront, and IAM.
• Document upload with AWS S3 using presigned URLs to verify care services.
• Email notifications via Resend API.
• AI-supported care service search via OpenAI API.
• Implementation of complete user flows such as registration, login, password reset, and the placement process.
• Development of an admin panel for user and care service management as well as analytics.
• CI/CD with GitHub Actions and containerized deployments with Docker.
• End-to-end tests with Playwright.

Technologies: Kotlin, Spring Boot 3, Spring Security, JWT, JPA/Hibernate, PostgreSQL, Angular 17, TypeScript, RxJS, AWS (EC2, ECS, S3, CloudFront CDN, RDS PostgreSQL, IAM), nginx, GitHub Actions, Playwright, Maven, Git, OpenAI API, Resend API, Docker, Scrum, i18n (DE/EN/TR), Kiro, feature flag architecture.

• Technical leadership across hardware, firmware, and software teams; scope: hardware/firmware team (4 people) and leadership group (5 people)
• Consolidated and documented a product family that had grown over more than 15 years and aligned it with CRA compliance — from the bare-metal I/O module to the cloud interface.
• Provided the most important customer product with the essential requirements and architecture documentation within two months — for a firmware landscape that had grown over more than 15 years. It now supports the customer’s modernization strategy.
• Established a monthly reporting line to the supervisory board and executive board within three months: nine meetings since 12/2025. The report itself is versioned and built from the CI pipeline; it is based on automatically collected activity and release data instead of assessments.
• Built a container-based CI/CD infrastructure from scratch: cross-compilation, host tests, and documentation builds in one continuous pipeline.
• Introduced declarative QA gates for DevOps and development artifacts — from the start using lefthook instead of pre-commit, executed in a dedicated container image.

Technologies used: arc42, req42, tpo42, docToolchain, PlantUML, ArchiMate, C4 model, ADR, C, C++ (GTest), CMake, Bare Metal (ARM Cortex-M3/M7), OCI containers, Jenkins, lefthook, Prometheus, Grafana, SBOM, CRA, OPC, SCADA, PLC integration, IPv6 migration, Zero Trust, Sociocracy 3.0, Cynefin

Temporary employment

• System black-box integration tests (BBIT, IVVQ): Execution of regression, release, confirmation and conformity tests for safety-critical braking control units in the railway industry
• Software Test Application & Integration: Runtime configuration of software components and libraries, validation of interfaces, configuration dependencies and component interactions
• Test Automation (FEAT Framework): Co-development and further development of an automated test framework for test execution, reporting and result analysis
• Functional Safety (SiL4, FuSi): Ensuring compliance with safety requirements, traceability and coverage as well as conformity with EN50126/28/29
• Test Automation for Communication Components: Configuration and validation of fieldbus (CAN) and Ethernet-based TCMS data communication interfaces (TRDP and CIP)
• Requirements Analysis & Shift-Left (PTC Windchill ALM): Analysis of software and system artifacts to identify gaps, ambiguities and redundancies early in the SDLC
• Test Design & Test Case Development: Derivation of test conditions and coverage strategies and implementation of data-driven test cases (DDT) including reusable test data fixtures
• CI/CD & Automation (Python, PowerShell, Jenkins, SVN): Automation of build, test and HIL deployment processes as well as integration into CI/CD pipelines
• Test Data & Configuration Management (XML): Maintenance and adjustment of XML test vectors and system configurations with automated integration into test environments
• Non-Functional Testing: Execution of performance and load tests to assess stability and system behavior
• Agile Development & Defect Management (JIRA, Confluence): Work in Scrum teams, test coordination, review of test artifacts as well as defect tracking and root-cause analysis
• Error Analysis & Debugging (CANoe, CANalyzer): Analysis of errors and message flows across multiple system levels (application to bus)
• Model-Based Analysis (UML, Enterprise Architect): Specification of SUT/SOW and support for systematic test control
• Process & Test Documentation: Creation of integration and test documentation according to internal quality and certification requirements

Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.

• Designed and operated a highly scalable microservice and serverless architecture
• Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
• Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
• Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
• End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
• Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
• Robust backup and disaster recovery strategies
• RDS Postgres backups and hourly snapshots
• Read-only, asynchronously synchronized replicas with automated master failover in emergencies
• Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
• Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
• Integrated Stripe for international payment processing
• Built a marketplace payment system with multiple parties and payout routines
• Used Algolia for high-performance real-time search of digital assets on the platform
• Federation of services with GraphQL and Hasura
• Later migration to GraphQL Mesh
• Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
• Used Next.js / React for modern frontend applications in the nx monorepo
• Enterprise security architecture & access control
• Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
• Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
• Built internal microfrontends with Retool for fast prototyping and operational business processes

Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest

• Opt-in RAG extension over tenant-owned data sources (SharePoint, Confluence) on existing multi-tenant enterprise AI platform
• Architecture: ADRs, solution evaluations, permission strategy, cost modeling
• End-to-end SharePoint and Confluence connectors: OAuth consent flows, token refresh, metadata sync, search integration
• Permission resolution: ACL indexing at ingestion and query-time verification (document-level security)
• Elasticsearch hybrid search (semantic + keyword) with RRF scoring
• RAG chat with context injection and source citations
• Stack: Elastic Cloud, Elasticsearch, Docker, Northflank, Next.js, React, TypeScript, Prisma, Microsoft Graph API, Atlassian REST API, OAuth 2.0