Site Reliability Engineering Experts in Germany

• Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
• Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
• Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
• Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
• Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
• Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
• Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
• Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.

• Designed and developed the architecture of an enterprise SCM/CI platform for Kubernetes-native delivery and GitOps workflows.
• Implemented infrastructure automation and Vault & IAM integration for secure, compliant pipelines.
• Coordinated cross-functional teams to improve DevOps, security, and architecture in release processes.
• Increased platform adoption and developer experience by automating onboarding and artifact pipelines.

• 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

• Drove two cross-functional engineering teams within the SAFe framework to deliver backend and integration solutions for Visa’s Terminal Management and Cybersource Onboarding platforms
• Served as Program Coach for ten teams within the Platform Services organization, advancing Agile maturity, delivery alignment, and a culture of continuous improvement
• Orchestrated Agile ceremonies including Product Manager syncs, metrics reviews, inspect-and-adapt sessions, system demos, and leadership workshops to strengthen transparency, collaboration, and delivery performance
• Championed the rollout of the Re-imagine Work@Visa scaled delivery framework within the Agile Transformation Team, improving collaboration and delivery predictability
• Increased release frequency 18× per quarter by synchronizing distributed teams and developing a comprehensive release guide
• Partnered with the Release Manager to standardize deployments across Visa Data Center, AWS, and Mobile platforms
• Led teams to close all security findings and embed remediation into BAU, achieving zero open issues by mid-2024
• Directed the Security Findings Program across the portfolio, ensuring visibility, accountability, and progress tracking
• Supported the roll out of the OKR framework and led quarterly reviews to align execution with business goals
• Strengthened communication across distributed teams, removed blockers, and advocated for continuous improvement and automation
• Delivered on demand workshops for teams with raising maturity and adoption of best practices
• Co-founded a Center of Excellence and Agile Community of Practice to promote continuous learning and alignment
• Partnered with SRE and InfoSec teams on multi-region rollout and security initiatives to enhance reliability and compliance

• 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

• Adaptation, optimization, configuration, and administration of a multi-stage GitLab instance with over 250 users
• Setup, adaptation, expansion, and optimization of infrastructure, configuration, and monitoring
• Provisioning of services and handover to production
• System environment: DependencyTrack, GitLab, Grafana, Hedgedoc, Kubernetes, Oauth2 Proxy, Openstack, Prometheus, Syseleven

Advising tech companies and founders on product strategy, customer discovery, AI-driven product development, and product operating models.

• PRISMA project
• Ansible automation
• Windows third-level support for Windows NT, Windows 2000, Windows 2013, Windows 2016, Windows 2019

• Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
• Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
• Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
• Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
• Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow

IOG (IOHK), is one of the world's pre-eminent blockchain infrastructure research and engineering companies.

• Converted a lingering R&D project into a cohesive, production-ready testnet; built and scaled the 35-member engineering team (Core, QA, SRE) to achieve this goal.
• Defined strategic direction and aligned technology development with business objectives as a key member of the leadership.
• Optimized software development processes and implemented agile methodologies, enhancing operational efficiency and code security.
• Delivered projects in a fast-paced startup environment through effective project management and resource allocation.

• Building a cross-functional product team to develop a super app
• Advising and mentoring to support the team and provide input (technical & soft skills)

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.

• Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Umweltbundesamt with SIEC)
• Development of Python APIs and web applications, deployment on AWS/ECS with Terraform
• Collecting power consumption metrics for servers, CPUs, GPUs running AI workloads
• Technologies used: AWS, EC2, ECS, Fargate, CloudMap, VPC, Route53, Lambda, EventBridge, CodeBuild/CodePipeline/CodeDeploy, Terraform, Docker, Linux, Bash scripting, Python, Flask, SQLAlchemy, SQL, MariaDB, InfluxDB, Telegraf, Prometheus, Zabbix, Kubernetes, Letsencrypt, certificate management

• Backend development: .Net 8, C#, PostgreSQL, Entity Framework Core, REST Web APIs, Docker, Kubernetes, Kafka, Open API Swagger, Apache Airflow, Resharper, Git, Microservices, SOAP, gRPC, Hangfire, OAuth 2, GraphQL
• Interface development for document processing with SmartFix, Softexpansion and Natif.ai: C#, REST API, Resharper, Git
• Deployment: Azure DevOps YAML, Vanilla Helmchart, Rancher, Kubernetes Cluster, Linux Docker, Windows VM, Python
• Unit tests and integration tests
• Telemetry, Kibana, Grafana, Elastic Search
• Work in a Kanban team of 8 developers, 1 tester and one Product Owner