CI/CD Experts in Frankfurt

• Functional requirements management for DIVID, the Umweltbundesamt platform for administering the single-use plastics fund. Focus: entitled parties, sub-entitled parties, and benefit reports.
• Consolidation and analysis of specifications, Jira, Confluence, functional concepts, and UX designs. Independent structuring and delimitation of requirements, as well as identification of contradictions, gaps, and dependencies.
• Creation and quality assurance of implementable user stories with clear, testable acceptance criteria. Preparation of decision alternatives and coordination with business, development, UX, and QA through team refinement.
• Conducting manual and technically assisted accessibility tests. Coordinating findings with QA and the Product Owner for further planning and implementation.
• Result: more consistent requirements, clearly defined processes and stories, and transparent open decisions. Separation of assumptions from confirmed requirements; better basis for implementation, refinements, and QA test cases.

Tools used: Jira, Confluence

• Hands-on development of AI-native product prototypes with specialized AI agents for research, requirements, business logic, UX/flow design, test case generation and quality assurance.
• Structured use and orchestration of AI agents through clearly defined roles, inputs/outputs and handover points; breaking down complex product tasks into verifiable work packages and iterative prototyping cycles.
• Establishment of human-in-the-loop quality gates to validate AI-generated results for functional correctness, consistency, completeness and feasibility; targeted rework cycles in case of deviations.
• Development of a regulatory GenAI/rules prototype for CRD VI with a structured decision flow, web UI, rule-based validation and automated test cases; iteration of the business logic through to a pilot-ready POC.
• Design of an AI-to-Action banking prototype: AI intent → consent → bank/product logic → conversion including admin console; translating the product idea into MVP scope, role model, user flows and clickable prototypes.

Design, development, and market launch of digital products and platforms – from strategic alignment and agile implementation to Go-to-Market and Go-Live, integrating AI into processes and products

• Completed the integration of log sources into Microsoft Sentinel, including GCP workloads – centralized consolidation of all security-relevant events from Azure and GCP environments for complete end-to-end telemetry and comprehensive compliance evidence
• Developed custom rules and use cases based on the GFG Use-Case Library and the MITRE ATT&CK Matrix to cover company-specific threats and GFG-relevant scenarios with precise, mapped detection rules
• Tuned detection rules to minimize false positives, optimized detection thresholds, and modeled exceptions – enabling the SOC to work with relevant, prioritized alerts while reducing Mean Time to Detect/Respond
• Built SOAR capabilities in Sentinel by developing playbooks to automate recurring response processes such as containment, user and host isolation, and ticketing – shorter response times and 24/7 scalability
• Designed and built a log transformation solution to normalize and enrich incoming raw logs (GeoIP, CMDB, threat intelligence) and convert them into a consistent schema for high-performance KQL queries, use case logic, and correlations
• Managed Azure security through Azure Policies to enforce security and compliance standards, prevent drift, and continuously remediate deviations
• Operated the Defender XDR portal to link endpoint, identity, email, and SaaS signals with Sentinel findings, enable holistic incident triage, and orchestrate measures directly from XDR

Technologies: Microsoft Sentinel, Microsoft Defender XDR, Azure Policy, KQL, GCP, MITRE ATT&CK

• Supporting the International Web Presence of the BA (IntWeb) project in the area of quality management, with the aim of taking responsibility for the quality of processes and project results while considering BA standards. The main objectives of the project are to give professionals abroad a quick overview of their opportunities for moving to Germany and to enable them to take the necessary steps consistently and with digital support by providing access to services.

• Defining the general guidelines in the QA handbook

• Summarising test results in QA reports for PLA

• Analysing project results for improvement opportunities

• Quality management of requirements analysis (particularly processes, methods, and tools)

• Ensuring compliance with SERA requirements

• Creating a cross-project test concept

• Agreeing on sprint completion reports

• Formal review of work results in accordance with requirements and/or the project plan

• Contact person for internal audit, external audits by auditors, or BRH (Federal Court of Audit)

• Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes

• Designed and implemented modular AI assistants for sales and business processes within the Microsoft ecosystem (Agentic AI, Copilot extensions)
• Frontend architecture and development with React + TypeScript for embedded chat and assistant surfaces (streaming UI, Hooks, React Query, OpenAPI clients)
• Enterprise-level agent development: reusable skill/agent library, MCP servers, review and compliance gates
• LLM integration into the user experience: Anthropic (Claude), OpenAI, tool use, RAG pipelines, prompt engineering, guardrails
• Architecture and code review consulting, and mentoring within the AI development team
• Integration with Microsoft Graph, Power Platform, and Azure services
• Technologies: React, TypeScript, Anthropic Claude, OpenAI, MCP, RAG, Microsoft Graph, Power Platform, Azure

The Base Services of DB InfraGO form a central data hub between the company’s IT systems. Common Data Services are developed that distribute data from source systems to a variety of downstream systems (via JMS) and make them available (via REST API). The existing service landscape based on TIBCO is being migrated to DB InfraGO’s cloud-native platform.

• Architecture design and implementation for performance-optimized bulk data processing of several million datasets at specific times during the day
• Technical specification and documentation of business requirements
• Integration of various subsystems (including SAP and Salesforce) through the reimplementation of more than 40 microservices based on Spring Boot
• Migration of TIBCO Based microservices from the Enterprise Integration Platform to the Cloud Native Platform using Spring-Boot
• Establishment of a deployment pipeline using GitLab CI/CD, Artifactory, and automated deployment to a Kubernetes environment with the help of ArgoCD
• Definition and implementation of automated unit, integration, and regression tests

Team Size: 9

Technologies/Tools: Java, Spring Boot, ActiveMQ(JMS), JUnit, Tibco Business Works, Gitlab (CI/CD), Kubernetes (Amazon AWS), ArgoCD, postgreSQL, Oracle, Postman, Hoppscotch, openAPI, Sonarqube

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

Participation in the EU-funded MORANE-2 project to validate the Future Railway Mobile Communication System (FRMCS) in real-world use cases: preparation of the requirements specifications for TOBA and the associated test specifications.

Technologies: 5GS (Radio & Core), FRMCS, MCx (MCPTT, MCData, MCVideo), MC Gateway UE, MCx Priority/Security/QoS Management, ETCS, SIP, IMS

• Built an MCP (Model Context Protocol) layer for Mwanachama's agency service, turning domain manager methods into callable AI-agent tools. This included a composite tool that builds a full organization design (org chart, goals, workflows, RACI matrix) from one specification.
• Built the chat-driven agency builder (Wakala Studio and API), where an organization describes its structure in natural language and an AI agent uses those tools to construct and modify the live design.
• Added an insights service so an organization can review AI-agent interactions and completed work. Insights from that review feed back into solution design, gated by architect and user sign-off.
• Alongside this, designed and built the platform itself: ~20 Go microservices on PostgreSQL, Flutter and React clients, deployed on Kubernetes.
• AI agents scan the platform autonomously for security gaps and run scripted tests, covering API (Postman-style) and UI testing. The rest of the work stays supervised. No rogue agents, promise.
• Building an AI-native enterprise platform that structures organizational data, workflows and responsibilities for both people and AI agents.
• Models accountability through RACI, allowing human and AI participants to take different operational roles, including Responsible, Accountable, Consulted and Informed. AI agents can also take controlled approval roles where the organization assigns that responsibility.
• Extended the organizational and operational-risk themes from my Executive MBA thesis into software, making roles, processes and controls explicit and machine-readable.
• Structures enterprise context so LLM interactions use more relevant information instead of repeatedly processing large amounts of unstructured content.

• Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
• Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
• Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
• Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
• Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
• Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
• Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka

• Development and optimization of the RTL+ frontend application for SmartTV and set-top box platforms with React and Next.js.
• Key role in the technical coordination of developers within the team and in coordinating implementation.
• Central interface to adjacent teams to simplify development processes and improve cross-team alignment.
• Improved frontend performance, stability, and rendering behavior on low-powered devices in a restricted runtime environment.
• Implemented a frontend testing strategy with Jest, React Testing Library, and Playwright.
• Implemented accessibility improvements according to WCAG 2.2 and WAI-ARIA.
• Integrated Didomi Consent Management as a contribution to increasing ad monetization on streaming platforms.
• Used AI-supported engineering workflows with Cursor for structured implementation, refactoring, and faster problem solving.

Technologies used: React, Next.js, TypeScript, JavaScript, GraphQL, Apollo Gateway, Zustand, Tailwind CSS, Styled Components, React Testing Library, Playwright, Jest, HTML5, CSS3, AWS Lambda, EC2, CloudFront, S3, GitLab CI/CD, NX, Cursor

Statistical Forecasting Algorithm

• Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
• Migration from R/On-premise to Python/Snowflake
• Productionalization on Snowflake in cooperation with data engineers & DevOps

Monitoring Dashboard

• Data engineering for preparation & provisioning of necessary data/resources on Snowflake
• Development & deployment of a Streamlit dashboard in Snowflake

ML-based Probabilistic Forecasting on Vertex AI

• Development of a ML-based probabilistic forecasting algorithm from scratch
• Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI

Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow

• Co-built a full e-signature and identity verification platform in a two-person team with a senior backend developer, with no designer or PM: all product, UX, and scope decisions made jointly.

Next.js / TypeScript