Google Cloud Platform Experts in Munich

Marco Steidel

IT Interim Manager | Interim CIO | Transformation Lead | IT Project Manager & Program Manager | Digital Advisory Board Member

Grünwald

Last position:

IT Interim Manager & Digitalization Consultant at paarprojekt GmbH

Project management and consulting services with a focus on IT interim management: digitalization of corporate management, including processes and applications
Assessment of the entire IT infrastructure, including applications, core processes, and contracts, including cost optimization
Evaluation and introduction of solutions to support digitalization in the company in the areas of property management, CRM, invoice review and approval processes, smart metering, DMS, and time tracking
Digitization of file folders and introduction of SharePoint and Microsoft Teams as the central document and communication platform
Design and delivery of an AI workshop, including rollout of AI tools to increase efficiency and transparency in key business processes
Creation of training materials and delivery of user training for newly introduced digital processes and solutions

Michael Nelz

Senior ML Engineer | AI Engineer | Problem Solver

Eichenau

Last position:

Senior ML Engineer, AI Engineer at Lanxess AG

Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.

Vicenco Kenk

Interim IT Team Lead / IT Service Management / IT Project Management / Solution Architect

Brunnthal

Last position:

ITSM Project Manager (self-employed)

Unified ITSM framework

Definition of a company-wide ITSM target picture
Introduction of a uniform service structure across all business units

SLA and OLA management

Building a standardized SLA framework
Definition of service classes (Business Critical, Standard, Low Priority)
Introduction of OLAs between internal teams
Building meaningful SLA reporting
Definition of KPI and service dashboards for business units

Service portfolio management

Definition of service descriptions
If needed, preparing possible cost and service billing

Ticketing & processes

Incident management
Uniform ticket categories
Standardized prioritization
Escalation matrix
Automations
Self-service optimization

Request fulfillment

Service catalog across all business units
Approval workflows

Problem management

Introduction of root cause analysis
Known error database
Problem review process

Complete asset management concept

Hardware lifecycle management
Software lifecycle management
Leasing lifecycle
Mobile device lifecycle
Monitor lifecycle
Phone lifecycle

Processes

Procurement
Goods receipt
Inventory
Assignment
Return
Disposal
Leasing return Goal: single source of truth for all assets

CMDB design

Definition of all configuration items:
Workplace
Notebooks
Monitors
Mobile phones
Printers

Infrastructure

Servers
Firewalls
Switches
WLAN
Storage
Backup systems

Cloud

Azure resources
Microsoft 365
SaaS services

Relationships

User ↔ Asset
Asset ↔ Service
Service ↔ Infrastructure
Location ↔ Asset
Goal: make all service dependencies visible

Software asset & license management

License management concept
License balancing
Compliance reporting
Microsoft license management
Adobe license management
SaaS management
Contract management
Renewal management

Interfaces & automation Existing systems

Workday
Joiner
Mover
Leaver

TESMA

Leasing data
Contract data

Matrix42

Asset synchronization
User synchronization

Active Directory / Entra ID

User management

Microsoft 365

License assignment
Group management

Dormakaba

Access processes
Lifecycle services

Monitoring platforms

PRTG
Palo Alto
Cisco

Reporting & KPI framework

Definition of a management dashboard
KPIs
Ticket volume
SLA fulfillment
MTTR
First resolution rate
Asset accuracy
License compliance
Change success rate
Service availability
Degree of automation

Network redesign support

Governance
Support of the network redesign from an ITSM point of view
Definition of affected services
Change management structure
Communication concept

CMDB integration

Recording of all network components
Service mapping
Dependency analysis

Validation of documentation and knowledge base articles

Network documentation
Operations documentation
Standard changes

Monitoring & event management

Target picture
Central monitoring concept
Event management process
Alerting strategy
Escalation model

Systems

Cisco
Palo Alto
Fortinet
Rubrik
Veeam
Matrix42
Azure
Microsoft 365 Automation
Ticket creation from monitoring
Escalations
Standard actions

Audit, compliance & information security

ISO 27001 consulting
TISAX consulting
NIS2 preparation - consulting
Audit-ready processes
Documentation structure
Evidence tracking in Matrix42

Roadmap

12-month roadmap
Prioritization of all measures
Quick wins
Medium-term projects
Long-term target picture
Documentation

Tamás Eppel

Senior Software Developer / Tech Lead

Last position:

Senior Software Developer / Tech Lead at NDA (defense / OSINT)

Designing the audit logging framework
Implementing APIs for developers to integrate in their codebase
Implementing ingestion pipeline, database query layer and UI for browsing the audit events
Improving stability and reliability of the backend system

Philipp Grunert

Machine Learning & Data Engineer

Last position:

Data Scientist & ML Engineer at Data-Science Factory GmbH

Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
Implementation of automated end-to-end cloud processes
Development of LLM and NLP models
Creation of interactive reports
Support for national and international large corporations as well as medium-sized companies in implementing ML projects

Tezcan Dilshener

Solution Architect / Project Manager

Last position:

Solution Architect / Project Manager at German Football Association

Overall responsibility for the project lifecycle from scope definition to completion
Close collaboration with platform teams, IT leaders, and external service providers
Application of SAFe principles and structured sprint work
Creation of a migration roadmap with clear milestones
Monitoring of the lifecycle: onboarding, repository migration, replication of permissions, and system tests
Visualization of the architecture with PlantUML and Gliffy as well as documentation in Confluence
Regular status reports and running knowledge transfer sessions

Mirza Klimenta

Agentic AI for a DeepResearch project

Last position:

Agentic AI for a DeepResearch project at Freelance

Created a multi-agentic system supported by a knowledge graph to automate drafting of research papers
Used multiple experts (OpenAI models) collaborating during document drafting
Extracted useful information from the knowledge graph
Technologies: LangChain, LangGraph, Smolagents, LlamaIndex, dspy
Infrastructure: Terraform and GitHub Actions (CI/CD) on AWS
Deployed initial application as a Streamlit app

Thomas Hoefkens

Senior MLOps, DevOps Engineer

Last position:

Senior MLOps, DevOps Engineer at Trianel Energy

Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
Integration of RESTHeart to create a REST API for MongoDB.
Build an Angular frontend to simplify data queries and master data maintenance.
Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).

Damian Śniatecki

CTO

Last position:

CTO at FRATCH.IO

Managed end-to-end product development, overseeing the successful delivery of technical solutions.
Led and mentored a team of highly specialised technical professionals, fostering a culture of collaboration and innovation.
Oversaw the hiring process to build a talented and dedicated team.
Built a scalable and robust backend microservices system from scratch, designing and extending it to meet evolving business needs.
Ensured the system's high availability with a 99.99% up time, implementing resilient architecture and monitoring mechanisms.
Developed and implemented technical strategies, aligning them with business goals and objectives.

Any-Arlene Niyubahwe

Data Analyst · SQL · Python · Tableau · Power BI

Last position:

Co-Founder · Data Engineering & Backend at zirikana (Kirundi Bible Web App) – Civic Technology

Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.

Valery Khamenya

AdTech Engineer & Data Scientist

Last position:

Sr. Data Scientist & Engineer at Virtual Minds

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

Kai Zimmermann

Program and project management; Agile (method) coach; sales/partner manager

Last position:

Program and project management; Agile (method) coach; sales/partner manager at Google (in cooperation with Wipro Technologies)

Strategic consulting for the initiation and management of complex, multidisciplinary projects
Stakeholder management (project scheduling, requirements management, budget management, risk management) incl. cross-functional communication with implementation partners
Carrying out analyses and recommendations with the technical team and discussing them at C-level

Andreas Anding

Interim AI Lead & Digital Architect · AI operating models in regulated companies · Author

Last position:

AI Consultant & Digital Architect at TeamIntel

Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
Two-gate governance: agent deliberation + mandatory human approval, full signed audit trail; graduated autonomy model („internal → autonomous per skill“).
Verified knowledge graph („Company Brain“) with source evidence for every answer; own orchestration framework (Virtual Team Framework).
Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
Building the governance-focused multi-agent platform TeamIntel (see AI reference projects).

Serge Kalinin

MLOps (machine learning operations)

Last position:

MLOps (machine learning operations) at REWE Digital GmbH

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

Alexander Schwartz

Team Lead & Product Owner