Chief Technology Officers in Germany

Stabilizing an Azure/.NET landscape in live operation.

• Architecture, DevOps, and operational readiness; technical decisions under time pressure
• Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics

Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps

• Proactive support of management in business field development & innovation management

• New development of a suite of business applications for analyzing valuation, P&L, and market price risk data

• Automation of all internal and external business and work processes

• Development of AI-based and AI-supported ETL processes as well as data analysis

• Business use-case development

• Business and work process optimization

• Enterprise architecture management

• Sales data analysis and forecasting as well as capture

• Inventory management & reordering

• Supplier management and communication

• Customs processing & clearance

• Shipping handling & warehouse coordination

• Interface management

• Technologies used: Microsoft Office 365, Microsoft Teams, JTL-Wawi, JTL-WMS, OTTO Partner Connect (OPC), Amazon Seller Central, DHL Global Forwarding, Jira, Draw.IO, Java (8,17,21,25), Jenkins, SonarQube, Git, Gitea, Spring Boot, Spring Batch, Vaadin, H2, PostgreSQL, Docker, Local LLMs, Postman, JasperSoft Studio, JasperReports

• Team leadership: Prioritization and coordination of four cross-functional teams.
• Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
• Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
• Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
• Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
• Organizational development: Improving communication and decision-making structures across all organizational levels.
• Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
• Quality assurance: Ensuring high quality standards in processes, services, and deliverables.

• Product responsibility for the central platform "one" as a group-wide web-based customer portal
• Coordination of the connection of 20 group companies to the product platform
• Derivation and steering of a group-wide product strategy and roadmap aligned with company goals
• Prioritization and bundling of strategic requirements from the various group companies
• Harmonization of different interests and moderation of complex decision-making processes at management level
• Ensuring the technical and business integration of the product into existing system landscapes, business processes, and business models
• Building transparent governance and decision-making structures for group-wide product development
• Representation of the product towards internal and external stakeholders at leadership level

I designed and developed an AI-powered multi-tenant platform on Azure that transforms SAP process recordings into technical documentation, presentations and automated tests, processing over 15,000 process recordings for enterprise customers like Würth. I owned the architecture, the production releases and the DevOps setup. I also designed a multi-tenant system with SSO and role-based access on Azure. Implemented an MCP Server with Dynamic OAuth Authentication.

Main Tasks:

• Sprint planning and feature preparation
• Design the multi-tenant platform architecture (FastAPI, SQLAlchemy, PostgreSQL row-level security for tenant isolation)
• Develop AI pipelines with Prefect for transcription (Azure Speech API), document generation and SAP screen-recording analysis (Claude, gpt-4-mini)
• Design and implement an MCP server to expose tenant knowledge to LLM clients (Claude), with async retrieval and reranking
• Implement LLM cost tracking, rate limiting and client pooling for Anthropic/OpenAI/Azure OpenAI endpoints
• Set up CI/CD: Docker images to Azure Container Registry, GitHub Actions, Azure Static Web Apps, Alembic migrations in containers
• Manage production releases and execute live data migrations for enterprise customers
• Define engineering standards and architecture patterns for the team

Environment: Azure / Azure Foundry / Python / FastAPI / Prefect / React / PostgreSQL

Leading the technical vision and product strategy for a sovereign AI startup focused on European data infrastructure and compliance. Managing a cross-functional team of 7 across engineering, AI development, and operations in a fully remote environment.

• Defining the company's product and technology roadmap, including AI-powered solutions with integrated payment services
• Designing scalable platform architectures with emphasis on data sovereignty, security, and European regulatory compliance
• Driving hands-on development across the full stack while establishing engineering best practices and DevOps workflows
• Enabling developer productivity through mentoring, architectural guidance, and tooling decisions
• Shaping the long-term technical strategy to position the company for sustainable growth

• 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.

• Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
• Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
• Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
• Developed graph-based representations of product structures and dependencies for analytical reasoning.
• Designed and implemented an agentic AI framework for AI-supported decision workflows.
• Built scalable analytical microservices and integrated reporting through modern BI technologies.
• Coordinated backend, AI, and frontend development across the MYNR platform stack.

Strategic technology leadership and architecture consulting.

• Fractional CTO & interim management for startups, scale-ups, and enterprises – technical strategy, team building, architecture oversight, and delivery.
• Architecture consulting on cloud-native, distributed, and event-driven systems: reviews, design partnerships, and ongoing advisory.
• Event-driven architecture training – a hands-on 2-day course for engineering teams
• Conference speaker on distributed systems

Predapp is a Sovereign AI and Infrastructure company building AI systems that organisations can own, control, and deploy on their terms, with full data sovereignty. As CTO and investor since 2015, leading the development of the Sovereign AI Platform alongside an advisory practice spanning AI strategy for enterprises, fractional CTO engagements, and technical due diligence for VCs, PE, and family offices.

• Architected the Sovereign AI Platform from zero owning technical vision, infrastructure design, and engineering roadmap; currently deployed at a European hospital, an automotive client in Germany, and two US startups, with active commercial discussions with two leading European hosting providers
• Dubai Health Authority (DHA / Nabidh): Designed and trained AI symptom checker and triage system for national 'Doctor for Every Citizen' initiative under HH Sheikh Mohammed bin Rashid Al Maktoum
• Emirates Airlines: Designed and deployed AI agent for ground personnel accelerating training, improving issue handling, and reducing cost of liquid workforce
• Developed explainable AI triage system piloted at University Hospital Heidelberg and Famagusta Hospital (Cyprus); reduced patient wait times by up to 15% (validation ongoing)
• Built production scheduling engine for US industrial AI startup: RL + Monte Carlo tree search, reducing planning from hours to seconds
• Designed and led the development of semantic search engines using RAG + Knowledge Graphs; developed Agentic Text-to-SQL solution for citizen data scientists
• AI strategy advisory and readiness assessments for enterprise clients, including architecture reviews, maturity assessments, and AI roadmap development

• Designed and led multiple CRM and CX transformation initiatives for global B2B organizations.
• Co-created strategic CXO use cases with ServiceNow and Salesforce.
• Developed the “BackOnTrack” and “Optimizer.Club” frameworks to rescue underperforming programs.
• Delivered +15% average margin improvement and saved up to 60 PD per engagement.
• Built and led agile, cross-functional delivery teams in regulated and asset-heavy industries.
• Supported executive boards with CX maturity models, platform strategies, and KPI-based governance.

Software service provider for AI solutions, automation, and custom software.

Team: built from 2 to 10 developers, 8 direct reports, partly remote · Portfolio: 6 parallel projects (€25k–€250k), scaling > €1M

• Ensured delivery capability for 6 parallel customer projects: role model, capacity planning (510–660 productive person-days/year), hiring roadmap with €380k–€440k/year personnel budget
• Established SDLC framework from scratch in under 6 months: REQ/SPEC structure, V-model gates, GitHub Issues as specification, Definition of Done, release process; consistent, auditable development process across all customer projects
• Prepared large program (3,000–4,000 person-days over 18 months) for decision readiness: AI-native industry platform for the construction sector; scoping, team profile for 8–10 developers, phase 0 budget €390k
• Designed and introduced self-hosted AI platform: vLLM, LiteLLM, Qdrant, Supabase; agent architecture, MCP integration, OCR pipelines; prepared GPU investment with break-even model (month 15–16)
• Systematized presales end to end: lead qualification with maturity scoring, discovery workshops, own sizing model, costing with loaded hourly rates, structured handover to development
• Tangibly improved the security level of a customer platform: penetration test incl. re-verification of all findings

• Situation: Inherited a patchwork of aging proprietary systems accumulated over 20+ years — custom-built shop, pharmacy operations, logistics, and product data management. No standardization, no automation, no modern delivery practices.
• Team: Found a centralistic hero culture with one manager handling more than 20 direct reports. Removed the bottleneck, replaced low performers, brought resistant team members back on track or managed them out. Hired fresh talent that brought new energy and capability.
• Delivery: Unified nine brands into a single platform, improving delivery speed by roughly 10x and eliminating cross-brand inconsistencies. Launched a new mobile app that tripled mobile revenue share within 12 months.
• AI: Implemented AI coding tools across development departments. Continuously working on trainings and knowledge sharing for developers. Delivered analytics and agentic automation for customer care inbound emails, and initiated agentic call automation.
• Operations: Introduced automated build and deployment pipelines, initiated cloud migration, and brought the core pharmacy system onto a maintainable, current foundation.
• Governance: Took back project prioritization from ad-hoc business demands by introducing transparent capacity planning — the biggest “no” enforced and the most impactful change for the organization.

• Founded Latence to commercialise runtime safety patterns from HALO as a deployable product.
• Built end-to-end as single technical founder with open-source stack on NVIDIA ecosystem.
• Developed TRACE: real-time safety layer for knowledge agents and RAG pipelines with groundedness scoring, prompt-attack detection, GDPR redaction, context compression, audit-ready traces.
• Developed vLLM Factory: production inference framework on vLLM with custom Triton kernels and 12 parity-validated plugin models, achieving up to 11.7× throughput vs vanilla PyTorch.
• Developed ColSearch: single-node multi-vector late-interaction retrieval engine with Rust SIMD and fused CUDA, achieving 3.12× FastPlaid geomean QPS on BEIR-8 and a 1.58-bit quantized lane 6.4× smaller than FP16.
• Developed llm-opt: LLM compression research framework with hierarchical importance, structured pruning, tabu search, knowledge distillation.