AWS CodeBuild Experts in Germany

traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.

As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.

• Design and implementation of event-driven backend services.
• Migration and replacement of legacy processing pipelines.
• Development of replay / rebuild mechanisms for large event datasets.
• High-throughput asynchronous event processing on SNS / SQS.
• Database and query optimisation for PostgreSQL and DynamoDB.
• Design of scalable read / write models and aggregation pipelines.
• Production troubleshooting and operational support.
• Performance tuning and infrastructure scaling.
• Design and stabilisation of integration and system tests.
• Technical concepts, architecture documentation, and cross-team collaboration.
• Support the further development of existing GitLab CI/CD pipelines

Geofence & Wagon Stay Processing

• Algorithm to detect vehicles within geofences (entry, exit, dwell time).
• Event sourcing with guaranteed chronological order within the affected time window.
• Refactored geofence event and wagon-stay processing logic for performance.
• Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
• Repair and replay tooling for corrupted or inconsistent movement data.

Fleet Metadata & Mileage

• Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
• Scalable mileage aggregation and replay mechanisms.
• Read / write models and optimised queries for high-volume mileage calculations.

Sensor & Telematics Integration

• Integrated telemetry and sensor processing pipelines.
• Snapshot and state-calculation logic for sensor systems.
• APIs and persistence models for wagon sensor data; data-quality improvements.
• Further development of a service using gRPC for intra-service communication.

Movement Segment Processing & Routing

• Migrated services to new movement-segment event streams.
• Built replay and rebuild tooling for segment correction.
• Optimised throughput and reliability for high-volume event processing.

Condition Monitoring & Wagon Analytics

• APIs and backend services for wagon condition monitoring.
• Brake-wear prediction processing and wagon analytics functionality.
• PostgreSQL views and optimised query models for operational dashboards.

Operational Reliability - First Responder

• Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
• Tuned database performance and AWS infrastructure under production load.
• Improved observability, monitoring and operational tooling.
• Supported rollout strategies, monitoring and post-deployment stabilisation.

• 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.

• Designed and developed a high-performance internal resource management platform using React and TypeScript, optimizing dynamic data rendering and state management.
• Built a React Native application to support mobile access to internal tools, enabling on-the-go project tracking for field teams.
• Developed custom 2D canvas-based visualizations using Pixi.js to simulate material flows and refractory layer behaviors.
• Integrated Pixi.js with React components for interactive diagrams and real-time UI updates.
• Developed interactive 3D visualizations using React.js for displaying refractory product layouts and simulations, supporting engineering and sales teams with dynamic product previews.
• Integrated Three.js within the React ecosystem to allow manipulation of 3D models in real-time via browser, enhancing user engagement and field configurability.
• Integrated a headless CMS to enable dynamic content updates by non-technical users, reducing content deployment time by 40%.
• Led AWS CloudFront optimization initiatives, improving portal load speeds by 30% globally.
• Actively collaborated with cross-functional Agile teams and product owners to deliver prioritized features with a fast feedback loop.
• Key Technologies: React.js, React Native, Three.js, TypeScript, Contentful CMS, AWS S3/Lambda/CloudFront, Cypress, Agile Scrum

• Supporting the DevOps team in Terraform-managed, multi-region AWS infrastructure to achieve environment parity.
• Developed end-to-end CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy, automating the build and deployment.
• Maintained pre- and post-deployment scripts to automate critical tasks such as database schema migrations and environment sanity checks.
• Implemented CI/CD flow specifically for hotfixes via separate Git branches, managing back-merge activities from feature branches to release branches to ensure code integrity through automated conflict resolution.
• Deployed a dedicated, lightweight sanity check application hosted cost-effectively on Azure Container Apps to run automated health and basic functional checks as a post-deployment activity triggered via pipeline.
• Investigated production incidents through code changes and AWS CloudWatch logs.
• Coordinated integration of Dynatrace APM and its APIs for monitoring purposes.
• Full stack QA strategist for a high-traffic e-commerce platform built on a layered architecture for the back-end testing of core platform services, especially the order management system in Zed and Glue layers.
• Managed automation activities, testing process, and refactoring practices.
• Responsible for framework migrations, setup, and training for new automation frameworks.
• Promoted a shift-left approach within the QA team and created the test concept.
• Participated in meetings with IT managers, business owners, product owners, and team members.

• Delivered AWS-authorized content through AAI program
• Facilitated group and 1-on-1 mentorship sessions
• Coached non-technical learners into cloud career paths
• Created learning materials aligned with AWS Skill Builder and AWS Academy labs

• Co-authored enterprise cloud strategy including security and governance frameworks for 5 subsidiaries, and implemented part of the governance automation.
• Performed regular cloud cost optimization reviews across 10 teams resulting in ~20% cost reduction.
• Led the technology selection for the migration of in-house CIAM for 25M+ accounts to a SaaS solution, and worked with the product team through the migration.
• Supervised the technology selection and designed the architecture and delivery pipelines for the multi-tenant digital news and sports publishing platform, enabling ~250 editors within ~6 months of development start.
• Led the implementation of a multi-brand design system from idea and technical concept to implementation and rollout, enabling rapid UI prototyping for new products in a matter of hours.
• Managed a team of 4 architects and accelerated the professional growth of team members.
• Technologies: AWS cloud, Microservices, Docker, Python, Kafka, JavaScript, TypeScript, React.js, Node.js, GraphQL, REST, Gitlab CI, Visual Studio Code, git.

• Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Federal Environment Agency 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

• Designed a hybrid AWS platform combining 10+ ECS Fargate microservices (Spring Boot) and Angular/React frontends with a serverless ETL pipeline based on Lambda, S3, SQS/SNS and DynamoDB
• Built a serverless notification service (Lambda + SNS/SQS) enabling event-driven workflows across microservices
• Automated all infrastructure using AWS CDK v2 with reusable constructs that significantly reduced provisioning time
• Implemented blue/green & canary deployments via GitHub Actions and CodePipeline for safe, repeatable releases
• Strengthened observability via CloudWatch and OpenSearch dashboards, alerts and standard runtime checks
• Developed backend services in Java (Spring Boot) and TypeScript with clean REST APIs for modern SPAs

• CVA6 MMU: formal verification using SVA
• CVA6 subsystem: IP integration, verification (UVM)
• Tightly coupled cache coherence for CVA6: RTL design and verification (SystemVerilog), FPGA prototyping (IP integration - CPU, LLC, DDR, Eth), Linux
• Verification of a laser controller on FPGA (medical, VHDL, VUnit, Python, C++ for Microblaze)
• Fault injection emulation on FPGA (SystemVerilog)

• Built advanced expertise in designing and deploying Model Context Protocol (MCP) infrastructures to enhance AI agent capabilities for an NGO.
• Developed and maintained MCP servers (e.g., using FastMCP) exposing external tools and data sources to LLMs via a standardized API (JSOB).
• Enabled seamless tool integration by adhering to an MCP client-server architecture, allowing AI hosts or agents to dynamically discover and invoke tools, access resources, and leverage custom prompts (file storage, SQL DBs, Weaviate, Chroma).
• Automated deployment (CI/CD) in AWS with infrastructure as code (CDK) and Jenkins (scheduler).
• Conducted comparative model evaluation to address German language needs (Hugging Face versus Anthropic, Cohere, others) and AWS Bedrock.
• Evaluated legal and regulatory considerations, ensuring MCP-based solutions complied with emerging EU AI Act requirements, such as risk classification, transparency, documentation, and responsible tool provisioning within the European context.