Scala Experts in Germany

• Short description: Lead a group-wide project to establish standardized cloud governance for Microsoft Azure, including policies, security and compliance controls, automation, and cost and operations control while preserving the autonomy of decentralized business units within regulatory boundaries.

• Tasks and activities:

• Overall responsibility for the design, setup, and implementation of an enterprise-wide cloud governance structure (Azure), incl. target picture, roadmap, and operating model.

• Management of internal and external stakeholders (C-level, IT, Security, Compliance, Cloud Architecture, DevOps) incl. decision-making and escalation management.

• Planning and facilitation of workshops on cloud strategy, governance principles, and the design of areas such as Identity, Connectivity, and Platform Management.

• Definition, implementation, and rollout of cloud policies (Azure Policy / custom policies), security standards, and compliance requirements (including GDPR, ISO 27001, BSI C5).

• Building a cloud governance framework aligned with the Azure Cloud Adoption Framework (CAF), incl. landing zone and guardrail concepts.

• Introduction of automation solutions for governance, security, and cost control (policy/control automation, IaC, CI/CD-based control mechanisms).

• Implementation of cloud security and compliance monitoring mechanisms as well as continuous improvement processes.

• Establishment and operationalization of FinOps in an enterprise environment (central and decentralized FinOps teams), incl. cost management strategies, reporting, and guardrails.

• Integration of governance policies into DevOps processes (e.g. CI/CD principles for security and compliance checks, GitLab Runner concept in spokes, GitLab CI/CD for CAF landing zones).

• Implementation of access concepts incl. RBAC design and "break glass" mechanisms (emergency access) as well as certificate automation (ACME / step-ca).

• Achievements:

• Created a unified, auditable governance and control set for Azure (policies, standards, compliance mapping) and thus laid the foundation for scalable cloud usage in a regulated environment.

• Established repeatable automation for governance, security, and cost control (IaC + CI/CD), reducing manual effort and implementation risks.

• Improved operational and decision-making capabilities across central and decentralized units (clearer roles, responsibilities, escalation paths, balance between autonomy and group requirements).

• Significantly increased workload compliance for lift-and-shift migrations.

• Technologies used:

• Microsoft Azure Policy, custom policies.

• Terraform, OpenTofu, Terragrunt.

• step-ca (ACME).

• Entra ID.

• Azure Firewall.

• Azure networking, hub-and-spoke architecture.

• Azure vWAN (evaluation).

• Azure Front Door, Azure Application Gateway.

• Azure ExpressRoute.

• Azure Key Vault.

• NetBox.

• GitLab (on-premises).

• Infrastructure, concepts used:

• Cloud shared responsibility model.

• Hub-and-spoke connectivity / central shared services (from a hub-spoke context).

• Central governance with decentralized delivery (business unit autonomy with guardrails).

• Methods used:

• Scrum.

• Stakeholder management (C-level to engineering).

• Cloud governance, Azure Cloud Adoption Framework (CAF).

• DevOps, CI/CD.

• Cost and FinOps approaches: tagging/chargeback models, budget/alert concepts, reserved instances/savings plans vs. on-demand scenarios, sensitivity analyses.

• RBAC, "break glass" concepts.

• ACME / certificate automation.

• GitLab Runner concept in spokes, GitLab CI/CD pipelines for CAF landing zones.

I designed and developed an AI-powered multi-tenant platform on Azure that transforms SAP process recordings into technical documentation, presentations and automated tests, processing over 15,000 process recordings for enterprise customers like Würth. I owned the architecture, the production releases and the DevOps setup. I also designed a multi-tenant system with SSO and role-based access on Azure. Implemented an MCP Server with Dynamic OAuth Authentication.

Main Tasks:

• Sprint planning and feature preparation
• Design the multi-tenant platform architecture (FastAPI, SQLAlchemy, PostgreSQL row-level security for tenant isolation)
• Develop AI pipelines with Prefect for transcription (Azure Speech API), document generation and SAP screen-recording analysis (Claude, gpt-4-mini)
• Design and implement an MCP server to expose tenant knowledge to LLM clients (Claude), with async retrieval and reranking
• Implement LLM cost tracking, rate limiting and client pooling for Anthropic/OpenAI/Azure OpenAI endpoints
• Set up CI/CD: Docker images to Azure Container Registry, GitHub Actions, Azure Static Web Apps, Alembic migrations in containers
• Manage production releases and execute live data migrations for enterprise customers
• Define engineering standards and architecture patterns for the team

Environment: Azure / Azure Foundry / Python / FastAPI / Prefect / React / PostgreSQL

• Freelance product owner, scrum master and agile coach in various projects spanning from local agencies to multinational corporations in diverse industries.

• Last projects:

• Adevinta: Technical Project Manager responsible for coordination of several sub-workstreams building the world’s largest classifieds multi-tenant platform.

• Aroundhome (a ProSiebenSat.1 company): Product Manager implementing and verifying on the business side a concept for digital qualification of user requests for matching service providers.

• Peek & Cloppenburg Düsseldorf: Product Manager Mobile advising on and guiding the rebuild of Android and iOS apps.

• Visual Meta GmbH (an Axel Springer company), Berlin: Director Product co-leading the Product & Engineering department together with the Director Engineering.

• Responsibilities at Visual Meta GmbH:

• Define and deliver a 3–5 year horizon product strategy including a product vision & mission connecting to existing company strategy and strategies from adjacent departments.

• Refine an existing OKR process together with OKR master and directors of other departments to increase focus and outcome.

• Support the Director Engineering in creating a platform transformation strategy to transform a monolithic on-premise tech stack into a service-oriented, cloud-based architecture and establish a domain-based organizational setup.

• Accountability for a motivated and talented team of 5 head-level colleagues and 17 operational team members from product management, data and UX/UI design.

• Key achievements at Visual Meta GmbH:

• Defined and delivered a 3–5 year horizon product strategy including a product vision & mission.

• Increased focus within OKR process by moving from 10 company-level objectives to 2 and from several hundred team-level key results to a few dozen.

• Created a career path framework for the product team defining roles and responsibilities from junior to head level positions.

• Assumed responsibility for backend architecture and technical strategy, planning and leading the platform's evolution in close collaboration with the CTO
• Simultaneously drove the development of new features for the housing and tenant management platform, balancing high-level architectural design with hands-on implementation
• Utilized AI-assisted workflows (with tools such as Claude Code, Codex, Cursor) and worked on AI-based features (with tools such as N8N, Mastra, ElevenLabs)

Technologies: Node.js, TypeScript, React.js, Next.js, PostgreSQL, Google Cloud, Docker, Kubernetes

• Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
• Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
• Automated extraction and training processes with CI/CD
• Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
• Developed and optimized embedded software for automotive control units
• Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
• Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
• Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
• Developed and trained machine learning models using PyTorch
• Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
• Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
• Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
• Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
• Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)

• Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
• Optimise k8s resources and integrate native Prometheus metrics with OPA
• Migrate from internal monitoring solution to Prometheus CRs + Dash0

Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana

• Development of high-performance ad distribution via auction
• Holistic (multi-campaign & multi-channel) advertisement placement optimization
• Algorithmic optimization for NP-Hard/NP-e
• Multiple Knapsack Problem with constraints
• Online estimation of parameters in stochastic environments

Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker

• 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

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

• Create an AI legal assistant with modern ML capabilities.
• Implement RAG architecture, with data pipelines for legal data search.
• Use AWS Bedrock for LLM and embedding models and LangChain/LangGraph
• Python with FastApi for backend and React for frontend

• Set up an operational contract information system. This is mainly used as an order management system - for migrating existing contracts as well as for creating and providing new contract bundles.

• Sales agents can use it to order new services, modify existing ones and migrate service types, as well as provide price information to the customer.

• This supports the marketing of new services as well as the replacement of old services for existing customers.

• In addition, existing data is imported, processed (ETL) and provided via services for further use in the portal front end.

• Analysis of the business and technical use cases (workflows, involved processes/systems, communication paths, security requirements)

• Further development / creation of the front-end components (React/JavaScript)

• Design and implementation of the business logic

• Creation of the functional and technical component documentation

• Test execution / test automation (Cypress, test coverage)

• Team size: 8 people

• Technologies: React, JavaScript, Rest (JSon), Yaml, Markdown, MariaDB (SQL), Docker, Swagger, Cypress

• Tools: Webstorm, ReactDeveloperTools, VisualStudioCode, Word, DBeaver, Git/GitLab

• Work management: GitLab

• Platform: Linux

• Build management: GitLab

Consulting and prototype work on AI voice and multilingual agent systems, using AI-assisted delivery across realtime translation prototypes, call-centre automation, and voice-to-voice consultation workflows.

• Built and advised on AI voice / agentic conversation prototypes, including realtime translation and consumer-facing consultation experiences.
• Worked across call-centre automation, voice UX, product architecture, implementation tradeoffs, and prototype development.

• Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
• Data and trade architecture development for liquidity provision

• Designed and implemented Azure Kubernetes Clusters, and managed DNS and Firewall solutions, enhancing network security and reliability.
• Led projects using Agile Scrum methodologies to streamline development cycles and improve project efficiency.
• Fostered and maintained relationships with suppliers to ensure timely project deliverables and resource availability.
• Managed continuous integration and delivery (CI/CD) pipelines using Jenkins, Sonar, GitHub, Bitbucket, and Terraform within the BMW Azure Cloud environment.
• Utilized Fortify SSC and Contrast AST for robust application security testing.
• Directed DevOps engineering initiatives on the SAP Business Technology Platform (BTP), focusing on streamlining development and deployment processes.
• Service Now governance, risk und compliance (GRC&IRM).