Multi-Cloud Experts in Germany

Industry: Publishing, media Project management for the concept of a RAG-based archive access solution: a secure on-prem or hybrid compute architecture for LLM and embedding operations, pipeline for transcription and automatic tagging, semantic search across audio and video archives. Use case evaluation and make-or-buy together with editorial team, archive, and legal department, taking into account copyright, broadcasting law, and the AI Act. Differentiator: practical LLM infrastructure experience from two own productive platforms combined with C-level program management in regulated industries.

• Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).

• Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.

• Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.

• Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.

• Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.

• Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.

• Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.

• CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.

• Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.

• Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.

• OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.

• Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).

• Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.

• Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.

• Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.

• SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.

• Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.

• Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.

• CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.

• Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.

• Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.

• Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
• Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
• Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
• Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.

Conversational AI assistant for cloud infrastructure and security queries

• Designed FastAPI backend with multi-turn conversation handler, token budgeting, and context window management.
• Integrated Amazon Bedrock (Claude 3 Sonnet/Haiku); built RAG pipeline with MongoDB chat history and semantic search.
• Implemented Factory Pattern for modular LLM provider switching; reduced model onboarding effort by 60%.
• Reduced LLM inference cost by 35% through model tiering (Haiku vs Sonnet) and prompt/entity consolidation.

Tech: Python, FastAPI, Amazon Bedrock, MongoDB, Streamlit, Pydantic.

• Holistic responsibility for modernizing and expanding federal networks and upgrading critical data center and telecom infrastructure in the high-security agency environment of BDBOS
• Planning and management of the expansion of national BOS network infrastructure in the VS-NfD/KRITIS environment with technical decision authority at the architecture and component level (Cisco, Layer 2/3, WAN redundancy)
• Planning, tendering (EVB-IT/UVgO) and oversight of the upgrade of security-critical telecom infrastructure for emergency call 110/112 (ACD)
• Capacity planning, rack integration, structured cabling, power supply, cooling concept (CRAC/In-Row) and DCIM monitoring for data center expansion
• Building the IT department from scratch: structures, governance, processes, team recruiting, vendor selection and long-term IT strategy
• Planning and managing infrastructure and application migrations: migration strategies, batch planning, hypercare stabilization and rollback concepts
• Creating vendor-neutral specifications (telecom systems, signature solutions) according to EVB-IT and UVgO; contract award and vendor management
• Setting up a secure IT environment according to BSI basic protection, ISO 27001 and VS-NfD; developing IT security concepts and CMDB analyses
• Hands-on program leadership: decision papers for management and steering committees, risk management, reporting and change request control

• 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

• 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).

• Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
• Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
• Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
• Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.

• Disciplinary and professional leadership of the IT and service team
• Definition and documentation of the Current Mode of Operation (CMO) in Confluence: application landscape, infrastructure, networks, backup & storage
• Development of the Future Mode of Operation (FMO) including process analysis & stakeholder interviews with all departments using BPMN and flowcharts
• Optimization of license management: reduction of ongoing software costs by approx. 17% p.a.
• Introduction and establishment of Jira as the central tool for project and service management
• Introduction and rollout of the HR software MindKey to digitize HR processes
• Introduction of a VoIP solution with Microsoft Teams incl. PSTN connection to replace classic telephony
• Introduction of the production and planning software OptiControl to digitize operational processes
• Rollout of Intune as a Mobile Device Management solution for Windows, iOS and Android
• Build-up of Power BI dashboards for machine park monitoring and financial reporting
• Planning and execution of the IT consolidation of two locations for 170 users
• Introduction of automated penetration testing with Pentera
• Coaching and mentoring the team in agile methods & project management
• Operational support in day-to-day business: administration, incident & change management
• Management of external service providers and assurance of the quality of outsourced IT services
• Responsibility for the IT budget incl. planning and controlling
• Direct reporting line to management with regular management reports on IT KPIs, budget and project status

• IaC & Automation: Designed and automated provisioning of about 40 Linux servers and cloud resources using Terraform and Ansible (reducing manual effort by over 80%).
• Container Orchestration: Built and operated two production Kubernetes clusters with 70+ Docker containers to ensure high availability, scalability, and self-healing.
• CI/CD Optimization: Developed and maintained 15+ CI/CD pipelines with Jenkins and GitHub Actions (shortening deployment times from several hours to under 15 minutes).
• OS Hardening & Operations: Automated patch management, OS configuration, and security hardening for 40+ Linux servers with Ansible to improve compliance.
• Monitoring & Alerting: Implemented centralized monitoring and alerting solutions for proactive issue detection and minimized system downtime.
• Cross-Functional Collaboration: Worked across Dev, Ops, and Security teams to establish DevOps best practices and infrastructure-as-code standards.

• Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
• Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
• Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
• Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
• Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
• Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
• Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
• Created and maintained dashboards in Power BI to provide actionable insights.

• Building an independent enterprise IT setup — cloud strategy, network, AWS landing zone, security requirements, contract negotiations.
• Migration of all applications; avoiding high contractual penalties for the client.
• Onboarding and coordination o...

• Guided a large-scale agile transformation, improving team agility, DevOps adoption, and cloud readiness.
• Supported DevOps & CI/CD practices to optimize cloud deployment strategies and reduce time-to-market.
• Led agile coaching initiatives to enhance cross-functional collaboration between IT and business teams.
• designed agile governance structures to align executive leadership with cloud and digital transformation goals.
• Technologies & Frameworks: Agile (Scrum, SAFe), DevOps, Cloud Adoption, IT Governance, CI/CD, Change Management

• Helped to design the AWS infrastructure, integrated services and backend architecture for use cases of an on-premise solution and partial migrations to AWS with fast response times
• Implemented automated AWS integration test suites
• Implemented mission-critical components and delivered them before the deadline in a production-ready state with operation and monitoring concepts
• This 2-month subproject was about building a data-intense pipeline (5 TB) to be enriched continuously with data
• Designed and implemented reusable AWS CDK constructs to be used across the company’s teams to enable faster onboarding with AWS
• Coached on AWS topics, distributed software patterns, security, domain-driven design, agile collaboration and documentation to improve performance and collaboration
• Technologies: AWS, GitHub Actions, ETL, monitoring, operations, TypeScript, Python, AWS CDK, CloudFormation, Java, Docker, AWS ECS, AWS Lambda, serverless, Jenkins, DevOps principles