Helm Experts in Berlin

• Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.

• Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.

• Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.

• Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.

• Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.

• Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
• Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
• Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
• Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
• Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
• Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
• Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
• Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
• Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
• Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

• Led migration to GCP using Terraform, GKE, and GitOps, improving deployment consistency and scalability
• Implemented Datadog observability stack via Terraform and datadog-operator
• Established automated end-to-end tests and on-call processes, improving incident response and service reliability
• Migrated from NGINX Ingress Controller to Kubernetes Gateway API (NGINX Gateway Fabric)
• Migrated stateful services (PostgreSQL and Redis) to GCP, improving scalability and operational reliability

• Support Authorization as a Service initiative for enterprise-scale authorization platform
• Incorporate comprehensive observability solutions into authorization infrastructure
• Provision and manage AWS infrastructure for authorization services
• Mentor development team on AWS and Kubernetes best practices
• Tech Stack: Java/Kotlin, Golang, Python, OPA, Spring Boot, AWS, Kubernetes, Terraform, ELK Stack, Prometheus, Grafana

• Delivered a new notifications platform implementation built from scratch to replace existing and upcoming services
• Collaborating with other teams to integrate more domains

Tech stack:

• Data: Scala 3, Apache Kafka, Python, Airflow, Astronomer
• BE-FE: TypeScript, NestJS, Java, Spring Boot, Vue
• Dev-ops: AWS, PostgreSQL, Docker, GitHub Actions, Kubernetes, Helm, ArgoCD

• Developed and deployed microservices in Kotlin and Spring Boot, integrated AWS Secrets Manager to secure credentials and decreased network calls using Spring cache.
• Refactored Kafka consumer using Spring Kafka with semaphore-based backpressure to cap records and keep heap memory stable under spikes; switched to batch upserts to cut down on database invocations; added Testcontainers integration tests for Kafka and database to pave the way for future changes.
• Automated the financial reconciliation workflow in Spring Boot (Kotlin) using Spring Scheduler, transactional boundaries, JPA/Hibernate on MySQL, and Flyway migrations, saving the accounts team 16+ hours per week.
• Designed and dockerized payments end-to-end test framework in Robot (Python) with reusable keyword libraries and profiles; integrated with GitLab CI (JaCoCo XML and HTML reports) to accelerate releases and lift code coverage to 80%.
• Implemented end-to-end observability on Datadog by instrumenting services with Datadog APM, correlating metrics and logs, provisioning dashboards, and creating monitors with burn-rate alerts and anomalies to harden reliability and give stakeholders clear visibility.

• Bootstrapping a CloudOps team and building a multi-cloud provider backend for a low-code Internal Developer Platform (IDP) with env zero

• Introducing user story mapping, ADRs, milestones, and backlog management

• Designing and developing core APIs, setting up CI/CD pipelines, OpenTofu/Terraform scripts

• Representing and communicating the team with third-party stakeholders (e.g. env zero)

• (Cross-)team coaching on DevOps, software design, Terraform, Golang, and agile practices

• Leading engineering organization of 45 engineers across 8 teams while serving dual role as Head of Backend
• Addressed critical organizational challenges including siloed departments, lack of engineering processes, and absence of technical strategy
• Executed comprehensive engineering leadership in people management, organizational design, and strategic planning
• Drove platform modernization including migration to a new Python backend, implementation of React micro-frontends, and transition to event-driven architecture
• Established engineering excellence framework through Architecture Decision Records, RFC processes, and comprehensive technology roadmapping
• Transformed engineering into integrated business partner by building collaboration channels with Product Management and Customer Operations teams
• Reduced escaped bugs by 50% and increased test coverage in legacy systems
• Achieved 100% Q2 roadmap delivery through realistic planning and improved estimation accuracy
• Introduced AI engineering strategy, establishing policies, providing tools, and training team on prompt engineering and agentic workflows
• Saved €10k monthly through infrastructure optimization including AWS IoT to RabbitMQ migration and decommissioning legacy systems
• Improved team engagement from 60% to 100% survey participation and enhanced eNPS scores among team leaders
• Built high-performance team through strategic hiring of Python, Go, and frontend engineers and improved onboarding
• Implementing transition to self-organized cross-functional teams

• Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
• Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator

• Project 1: Multi-Tenant SaaS Platform: Data Integration & Pricing Management
• Objective: New development of ELT pipeline (replacement for Java 6 legacy), integration of heterogeneous source systems (CSV, Excel, Email, external DBs), event-sourcing for complete auditability, multi-tenant architecture for tenant-capable data processing
• Challenge: Processing millions of records daily, audit compliance, data isolation between different tenants
• Solution: Stakeholder workshops for requirements analysis, event-driven architecture with Axon Framework and Apache Kafka, AWS services (EC2, S3, Lambda, SQS, API Gateway) for cloud integration, PostgreSQL with tenant-specific schemas for multi-tenant data isolation, REST API design with Spring Boot for external system integrations, comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit)
• Results: ELT performance improved from 30+ min to 1-5 min; 2-3 hours daily saved through workflow automation; 10-20 hours/week saved through event-sourcing auditability; 100% audit compliance; secure multi-tenant data isolation for 10+ tenants
• Project 2: Multi-tenant CRM System Modernization
• Objective: Migration of CRM system (20+ years PHP/MySQL) to Java microservices, Domain-Driven Design implementation, establishment of Test-Driven Development, multi-tenant-capable SaaS architecture for multiple customer tenants
• Challenge: Remodeling complex business logic, no existing test culture, scalable tenant management with data isolation
• Solution: Comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit), multi-tenant architecture with tenant-specific databases, REST API design with Spring Boot for cross-tenant integration, Kubernetes and Docker for container orchestration
• Results: 2× performance improvement; deployment time reduced from 40+ min to 5-7 min; migration without production outages; scalable multi-tenant solution for 15+ customer tenants
• Technologies: Java, Spring Boot 3.x, Angular, Apache Kafka, AWS (EC2, S3, Lambda, SQS, API Gateway), PostgreSQL, Axon Framework, Kubernetes, Docker, GitLab CI, REST API

• Leading the product lifecycle for sovereign AI platform and operating system teams for enterprise & government clients and internal stakeholders (infra, solution delivery, support, revenue)
• Built and scaled the platform from a 200-user beta to a full rollout of 70K+ members at the Bundesagentur für Arbeit (BA), secured with ISO 42001 and EU AI Act compliance
• Architected the shift to a multi-tenant shared inference, increasing GPU cluster utilization from 20% to 85% and reducing infrastructure cost-to-serve by 40% for SaaS clients
• Shipped model quantization, allowing clients to run advanced LLMs on legacy hardware (A100s GPUs) instead of the H100s, saving upwards of 70% cost per enquiry
• Abstracted complex Helm configurations into a dynamic model manager, reducing the time to install or swap models by ~80%
• Killed an expensive move to build own dashboard service, pivoting to an API-first data strategy that clients can consume directly and saving €100Ks in opex and capex
• Built a safety-first agent marketplace and control plane lighthouse project for a Tier-1 bank, allowing internal teams to deploy autonomous agents within strict regulatory guardrails

• Provide the Price Listing Service Team Price for all cars and vans in different markets
• Adjust market-specific requirements like taxes, government subsidies, campaigns
• Import, synchronize and store new prices for all new and existing cars in Redis datastore
• Support our product and handle on-call duties
• Daily operations, developing new features, bug fixing
• Pair programming, code reviews, mob programming
• Develop POCs for new ideas
• Maintain and extend the backend
• DevOps tasks
• Perform Kubernetes updates
• Adjust and further develop Kubernetes resources
• Develop and customize Helm charts
• Adjust and update ArgoCD
• Maintain, adjust and further develop CI/CD pipelines

• Developing GitHub Actions/pipelines for automatic application deployment
• Supporting the provisioning of Helm charts for the CI/CD infrastructure
• Rebuilding and migrating a Kubernetes cluster using Rancher
• Creating IaC with Terraform for Kubernetes and additional services (monitoring, databases)
• Deploying a highly available Percona Galera cluster (MySQL)
• Implementing a centralized monitoring and logging infrastructure

Projects:

Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:

• Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
• Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
• Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
• Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
• Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
• Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management

Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:

• Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
• Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
• Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
• Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
• DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
• Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
• Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git