Ansible Experts in Frankfurt

• 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

• 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.

• Linux server migrations: Planning and implementation of the migration with SLES Linux Deployment of VMs in VMware 8.0
• Guiding colleagues in configuring Linux VMs in vSphere Auto Deploy
• Application operations: Ensuring the smooth operation of applications on the migrated servers
• Operations manuals: Revising existing operations manuals, adding to them and creating new ones when required
• Reviewing service offerings: Adjusting and optimizing the service offering of external service providers
• Logistics SW, RedHat Linux, Ansible, Confluence / Jira

Project: SCS (Settlement / Clearing Services)

Settlement platform serving multiple trading and clearing venues — counterparty risk safeguarding, settlement volume reduction, central risk management, and post-trade anonymity.

Technologies: Java 17, Spring Boot 3, Microservices, Spring Data JPA, SonarQube, Fortify (SCST), Mockito, Jenkins, OpenShift, Maven, Podman, GitHub, JIRA, Liquibase, Swagger, AMQP, Apache Camel, Terraform, PostgreSQL, Instana, Graylog.

• Identified and remediated CVEs in third-party libraries using SCA tooling, strengthening the security posture of production components.
• Maintained 90% code coverage with SonarQube, improving code quality and reducing production defects.
• Enabled mTLS for database authentication and message broker connections, enforcing encrypted, certificate-validated communication.
• Designed and deployed microservices with asynchronous, REST-based communication between components.
• Optimized a high-volume REST API (~200K requests) by reducing response time from 3s to 2s (33% improvement), boosting throughput and reliability under production load.
• Automated build and continuous integration pipelines using Maven and Jenkins.
• Orchestrated containerized workloads on Podman/OpenShift and governed schema evolution with Liquibase, ensuring reliable, repeatable deployments across all environments.
• Optimized Java code and implemented EHCache-based caching, improving application performance.
• Streamlined release management by governing application images, JAR versions, and dependencies through DBAG Artifactory, ensuring version consistency and audit traceability across environments

• Designed a network management strategy focused on NetDevOps principles and model-driven telemetry using YANG data models
• Conducted NETCONF/YANG workshops for L2VPN/L3VPN services over SRv6
• Automated configuration deployment in the testing environment with Ansible
• Developed end-to-end service measurement concepts with IPSLA and the Telegraf-Prometheus-Grafana stack
• Created the dual-stack architecture design (router + switch + firewall) including a detailed test plan; planned, executed, and documented acceptance tests for the management network
• Performed BSI IT baseline protection checks according to the IT-Grundschutz catalog (needs assessment, modeling, risk analysis, deriving measures)
• Protocols: SRv6, IPv6, MPLS, BGP, ISIS, OSPF, NETCONF/YANG, model-driven telemetry, IPSLA
• Systems: Cisco Crosswork Network Controller, SolarWinds Orion, Grafana, InfluxDB, Telegraf, Ansible, Git
• Components: Cisco NCS router series, Cisco Catalyst switch series, Cisco Firepower firewall series

• Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
• Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
• Storage of the silver layer on Hadoop and the gold layer in Oracle.
• Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
• Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
• Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
• Versioning changes in GitHub and deployment via the CI/CD portal.
• Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
• Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
• Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
• Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
• Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.

• Platform established and running stably; deliberately reducing my involvement to refocus on an engineering mandate in the financial sector.
• Built an own SaaS learning platform from the ground up and scaled it to over 20,000 users (over 6,000 courses sold, B2C and B2B); end-to-end ownership from development through infrastructure to operations.
• Built a lab environment that provisions an isolated Linux container per user (Docker, Traefik, Go), including automatic provisioning and a dedicated subdomain per user.
• Integrated LLM features into the product and accelerated development end-to-end with AI-assisted workflows (Claude Code, Codex); CI/CD with automated tests.

• Testing the SekIDP and related components
• Test design, execution and automation, microservices, GitHub Enterprise, Eclipse, Katalon Test Platform, API Testing, Confluence 8, JIRA/Xray, Draw.io, Swagger/OpenAPI, Postman, Docker, Kubernetes, Podman, PuTTY, E-Health, Telematik, Gematik standards, EPA, E-Rezept, sektoraler IDP, encryption, XaDES, PaDES, DICOM, HL7, FHIR, IHE, ICD, SSO, SAML/Shibboleth, OAuth, smartcards, JWT, two factor authentication Android and iOS, Wireshark, BrowserStack, Cypress, gRPC, REST, SOAP, WS-Security, Linux Shell, PowerShell, SSH/SSL, Java, Kotlin, Cordova, Gradle, Groovy, Python, TypeScript

• Automation of the (Linux-based) web landscape maintenance.
• Use of SALT, SuseManager, Wildfly, scripting and Kubernetes.
• DevOps tasks and use of Jira.
• Management of "special" applications as well as creating and helping with concepts.
• Focus on security, maintainability, integration and tooling/integration.

• Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
• Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
• Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
• Use of Scrum and Kanban methods.
• Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
• Development of new plugins and add-ons needed on current infrastructure.
• Database support.
• Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
• Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
• Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
• Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
• Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
• Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
• Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
• Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
• Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
• Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
• Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
• Automated system provisioning and deployment using CloudFormation templates.
• Configuration of IAM roles, policies and permissions to ensure secure access control.
• Patch management, backup automation and disaster recovery setup on AWS infrastructure.
• Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
• Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
• Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
• Configuration of AWS CloudWatch to monitor application performance and system events.
• Planning and execution of migration of on-premises applications to AWS cloud platforms.
• Deployment of containerized applications using Docker and Kubernetes in AWS environments.
• Deployment of internal software packages between availability zones using AWS CodeDeploy.
• Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.

• Development of a central billing app for cloud costs at DB
• AWS
• Python
• AWS CDK
• RDS
• Spark (PySpark)
• Glue
• Lambda
• CI/CD (GitLab)
• React/Typescript
• data optimization
• Scrum

• Project management
• Building an internal IAM team
• Okta
• Project management
• IAM processes

• Supported implementation and operation of a portal used online and offline in customer-facing vehicles
• Automated processes by introducing CI/CD pipelines
• Provided enablement and methodological guidance for adopting software engineering best practices
• System environment: NestJS, Node.js, npm, AWS, Docker, Docker Swarm, GitLab CI, WhiteSource, PostgreSQL, Prometheus, Grafana, OpenSearch, REST API