Independent senior engineer for small and medium businesses
Hands-on Cloud Data & AI Agent Engineering
From reliable data pipelines to AI agents that do real work in your tools. Built and deployed in your own cloud, with no agency overhead and no vendor lock-in.
Data & AI Readiness Audit
A short, fixed-scope audit of your data and workflows that ends with a clear answer: what to automate first, what it takes, and what it pays back.
from €100
Fully credited when we sign the project, so the audit becomes free.
What I build
Pillar 01
Cloud Data Engineering
Clean, consolidated data on Google Cloud: automated pipelines from your CRM, ERP and apps into BigQuery, ready for reporting, automation and AI.
For example
- One revenue and customer view across CRM, webshop and accounting
- Automated data entry from emails and forms into a database
Pillar 02
Custom AI Agents & Workflow Automation
Task-focused AI agents that take real action in your tools: reading documents, updating your CRM, handling intake and support, with guardrails and human approval where it matters.
For example
- Lead qualification and intake agent that updates your CRM
- Customer support and booking agent connected to your calendar
Pillar 03
Private AI Knowledge Base
A private assistant that answers questions from your own documents with sources, hosted in your cloud in the EU, so company data never trains public models.
For example
- Support team assistant over product manuals and past tickets
- Policy and contract Q&A for operations, HR or legal
Ongoing
Support & Evolution Retainer →
Monthly hands-on support after launch: monitoring, fixes, model updates and new automations, from the engineer who built your system.
Why work with an independent senior engineer
Most AI initiatives stall because the data underneath is fragmented, or because a demo prototype breaks on real edge cases. I design, build and deploy the whole system myself.
Direct senior access
You work with the engineer who designs and writes the code from day one. No account managers, no hand-off to juniors.
You own everything
Code, pipelines, cloud project and keys stay with you. No proprietary platform and no monthly license markup.
Data first
Agents fail on messy data. I fix the foundation before building on it, so what goes live keeps working.
Guardrails built in
Narrow permissions, human approval for sensitive actions, logging and tests against your real cases.
EU hosting by default
Based in Germany. Systems run in EU regions and are designed around GDPR. Clients outside the EU are welcome too.
How an engagement works
01
Readiness audit
1 to 2 days
Review your workflows and data, rank use cases by ROI and scope the first build.
02
Prototype and evaluation
1 to 2 weeks
A working end-to-end prototype on your real data, measured against real cases.
03
Production deployment
2 to 4 weeks
Integration with your stack, CI/CD, guardrails, monitoring and logging.
04
Handoff and support
Ongoing
Full documentation and repository handoff, plus an optional monthly retainer.
Tools I work with
Frequently asked questions
Why hire an independent engineer instead of an AI automation agency?
With an agency you often pay for account management and get junior developers on the build. With me you talk directly to the senior engineer doing the work, iterate faster and keep full ownership of the code and infrastructure.
What does it cost to get started?
Every engagement starts with the Data & AI Readiness Audit, from €100. If we sign the project, the audit fee is fully credited, so the audit is free. You then get a fixed-price proposal for the first build.
Our data is messy. Can we still start with AI?
Yes, and it is the most common starting point. The audit shows what needs cleaning first, and Cloud Data Engineering makes the data reliable enough for agents to use.
Where is our data hosted?
In your own Google Cloud project, in an EU region by default. Your data is not used to train public models.
Do you work with companies outside Germany and the EU?
Yes. I focus on the EU and DACH region and work remotely with clients worldwide.
Background and expertise
Guiding Principles
How I work: grounded in the DAMA Data Management Body of Knowledge (DMBOK), so your information becomes a reliable and valuable asset.
Sovereign Cloud
An architectural perspective on data, operations and AI sovereignty in the EU.
Data Architecture
Why your data architecture is the true engine of your AI strategy.
ML Engineering
Operationalizing machine learning models on Vertex AI, from prototype to production.
Data Governance
A practical data governance framework and DAMA-aligned principles for data quality and security.
Related Reading
Ready to streamline your workflows?
Whether you need to fix a data pipeline, connect scattered systems or build your first production AI agent, start with a 30-minute call. No salespeople, just a direct technical conversation about feasibility, timeline and cost.
Book a Scoping Call