PRINCE2 Foundation

Interim leadership of a department within Sales IT with around 80 internal and external FTE, including 32 internal employees. Responsible for IT and financial portfolio management, project management, requirements engineering and agile coaching.

• Led four team leaders and two portfolio managers, supporting their development through professional and methodological guidance and coaching; also covered the Agile Coaching team lead role
• Further developed the methodology for prioritizing the IT portfolio and introduced mechanisms to align priorities with available budgets and capacity
• Set up a project to transition projects and development teams to a nearshore location: clarified goals and scope, defined the governance structure and responsibilities, and led the first team transition with 15 employees through to live operations
• Developed and aligned a concept to standardize and support budget planning, forecasting, reporting and ordering processes with tools
• Coordinated the introduction of Spec-Driven Development for requirements engineering in the context of Agentic AI; clarified roles across requirements engineering, business and development, and launched a pilot project
• Developed and aligned an AI maturity model and coordinated its organization-wide assessment

For two years, delivered three sessions on innovation, marketing and market entry strategy with a focus on China, as part of training for commercial and IT specialists

Process and structural optimization

Requirements:

• Optimize a procedures manual
• Improve organizational structures
• Better distribution of various tasks

Achievements:

• Developed a practical 7-step process model for mapping and optimizing processes for a trade business (SHK)

Migration from Microsoft Dynamics to a Multi-Cloud Salesforce Platform

• Lead of the Field Service stream in a programme replacing Microsoft Dynamics with Salesforce Sales, Service, Marketing and Field Service, including access for external contractors.
• Designed the end-to-end process from opportunity or case via work order and the Field Service mobile app to the service report.

Financial reporting as an MVP. Follow-up assignment.

• Reports on profit and loss, balance sheet and cash flow
• Budget and personnel metrics (FTE)
• Implementation as an MVP with a fixed scope

Transmission system operator – network provisioning platform (team lead)

• Designed the saga orchestrator in Python that provisions network fabrics with rollback.
• Split IP, identity, and resource allocation into bounded contexts with their own databases and typed clients.
• Implemented data access using DDD repositories and units of work, with no SQL in the domain code.
• Required integration tests using real PostgreSQL and RabbitMQ containers, and API fuzzing for every service.
• Introduced an agent workflow where a spec starts each change and a human approves every merge.
• Rolled out OpenTelemetry auto-instrumentation through GitOps across eighteen Kubernetes clusters.
• Led incident response for stuck provisioning and recorded every outage as a post-mortem.

Languages and software used: Python, FastAPI, Pydantic v2, SQLAlchemy async, PostgreSQL, RabbitMQ, Celery, pytest, testcontainers, schemathesis, Helm, Flux CD, GitLab CI, OpenTelemetry, pi coding agent.

Software product company – datacenter simulation SaaS (backend development)

• Built the asynchronous simulation pipeline as the second-largest contributor among more than twenty team members.
• Tagged every image by commit SHA and semver in the GitHub Actions deployment workflows.
• Diagnosed the RabbitMQ memory alarm that froze every simulation and fixed the limits in the Helm chart.
• Converted the test suite to function-style pytest, with coverage reported in every pipeline.

Languages and software used: Python, FastAPI, SQLAlchemy, Alembic, Celery, RabbitMQ, Redis, PostgreSQL, S3, EKS, Helm, Keycloak, GitHub Actions, pytest, mypy, ruff, SonarQube.

Internal AI platform – model serving and telemetry

• Built the FastAPI service that deploys open-weight models on GPU tiers as OpenAI-compatible endpoints.
• Upgraded production EKS by two Kubernetes minor versions and fixed zone-bound storage faults.
• Traced every model call, including its token count, cost, and latency, through the OpenTelemetry operator.

Languages and software used: Python, FastAPI, vLLM, LangGraph, pydantic-ai, OpenAI and Anthropic APIs, EKS, Helm, Flux CD, Terraform, GitLab CI, OpenTelemetry, Grafana.

Further Development of the Integrated Capacity Management Platform InKa

Rail Infrastructure

• Power BI shared datasets and reports via DirectQuery on Amazon Redshift (timetable, construction and capacity data)
• Automated report testing with Playwright in Docker containers, version control with GitLab
• Concept and implementation of user communication (information page, changelog, known bugs)

Initial Situation:

The integrated capacity management platform (InKa) is a monitoring and analysis platform for data from timetable and capacity management: customer orders, infrastructure, timetable operations, construction, as well as route capacity and width. The data is stored and linked in a structured data warehouse. This makes it possible to create complex KPIs across different source systems and display current and future route utilization as well as construction activity across the network. The goal is to improve strategic, medium-term and intra-year planning and provide users with easy access to capacity management analyses.

Measures:

• Enablement: Introduction of Power BI with training and workshops for development teams.
• Consulting & Design: Problem analysis, concepts and solution consulting for reporting requirements; implementation of reporting solution plans.
• Data Model: Development of shared datasets with DirectQuery on Amazon Redshift and import tables; DAX measures for utilization and capacity KPIs.
• Development: Data analysis, data transformation and visualization in Power BI; extension and migration of business applications to Power BI; AI-supported development in VS Code with GitHub Copilot.
• Test Automation: Automated testing of Power BI reports with Playwright; setup of the test environment in Docker containers.
• User Communication: Concept and implementation of a central information page with hot news, changelog and known bugs, access from reports with report filters, updates via Power Automate.
• Deployment: Management of Power BI Deployment Pipelines across the DEV, TEST and PROD environments.
• Agile Working: Work in an agile team according to SAFe (Scaled Agile Framework); refinement of user stories and features including effort estimates in Jira; version control with Git and GitLab.
• Quality & Documentation: Reviews for quality assurance, error analysis and resolution, technical documentation in AsciiDoc and Confluence.

Technologies: Power BI, DAX, Power Query, DirectQuery, Amazon Redshift, Git / GitLab, Deployment Pipelines, Playwright, Docker, AsciiDoc, Power Automate, Jira, Confluence, VS Code with GitHub Copilot, SAFe

Results:

• Capacity management KPIs from multiple source systems combined on one platform
• Transparency regarding current and future route utilization and construction activity across the network
• Easy access to analyses for users
• Automated regression testing of Power BI reports
• User communication implemented: central information page with hot news, changelog and known bugs, directly accessible from the reports

• Temporary cover for an absent non-financial risk officer.
• Operational scope: incident intake and follow-up, internal control testing, and first-line reporting for the Belgian entity.

• Talent Acquisition EMEA
• Development of scalable recruiting processes,
• Commissioning and management of executive search firms
• Direct Search,
• Active Sourcing
• Interviews

Independent advisory practice for strategy, organisational transformation, M&A / investor work and AI/data-enabled change.

• Short-term diagnostic and problem-solving mandates: rapid strategic and organisational assessments for leadership teams and Boards, translated into recommendations and transformation roadmaps.
• Organisational redesign and AI governance for an international group of approximately 1,500 employees: structure, mandates, decision rights and interfaces; AI-readiness and data-maturity assessment; vendor evaluation and selection; capability building.
• Design of a centralised Strategy Execution / Results Delivery Office for an industrial client: mandate, governance, portfolio steering, KPI logic, decision forums and implementation roadmap.
• Selected part-time mandate with SPARS GmbH (as a Business Development and Investments Director): developed M&A pipelines, assessed targets for strategic fit and synergy potential, led commercial due-diligence workstreams and investor / partner engagement.

AI Assistance and Target Vision for Partially Autonomous Energy Portfolio Management

Building an AI control layer directly on the up-to-date daily live portfolio of a large energy provider — not as an isolated pilot, but as an operational extension of the existing DB1 and portfolio management. The goal is the gradual development from assistance through monitoring/alerting to analysis agents with Human-in-the-Loop approvals, supplemented by a role-specific System of Engagement alongside the BI System of Record. At the same time, the business case, target vision and management pitch compared with static monthly reporting are being developed.

• AI control layer: Design and build on the existing live portfolio data product (several million contracts) — development stages assistance → monitoring/alerting → agents with Human-in-the-Loop approvals.
• LLM-supported data analysis: Semantic queries, SQL/tool integration and additional RAG components based on portfolio, plan-versus-actual and data quality data (Azure OpenAI, Snowflake), with drill-downs to individual contract level.
• Analysis agents: Multi-stage agents for variance and driver analyses of churn, price adjustments, volumes and procurement costs.
• Views concept: Role-specific interfaces for business units, management and C-level as a System of Engagement alongside the BI System of Record.
• Business case & pitch: Target vision and cost-benefit argumentation compared with static monthly reporting.
• LLM setup (privacy & security): Coordination with IT Security and Data Protection — EU region, data separation and approval processes.
• Agent architecture: Multi-stage agent pipelines (analysis → validation → summary) with documented data sources, tool calls, review steps and source references for each statement.
• Data foundation: Built on the up-to-date daily DB1 data product (Snowflake, dbt) — portfolio, plan-versus-actual and data quality metrics as the common basis for all AI analyses.
• Guardrails & evaluation: Evaluation and approval processes for LLM responses relating to management-relevant statements — test sets, metrics and human review.
• Prototyping & validation: Iterative validation of agent responses with the business unit — test question catalogue, feedback loops and response quality for each release.
• Roadmap & development stages: Detailed stages from assistance → monitoring/alerting → partially autonomous management, including transition criteria and governance for each stage.
• Integration: Integration into the existing BI and data landscape — BI remains the System of Record, while the AI layer provides interactive drill-down paths as the System of Engagement.
• Enablement: Enablement of business users — prompting guides, training and an operating model for ongoing use.
• Management: Coordination of business units, Data Engineering, IT Security and Data Protection.
• Change Management: Communication and expectation management with business units and management throughout the development stages.

Results:

• Built on an existing up-to-date daily data product with several million contracts
• Established an LLM setup coordinated with Data Protection and IT Security in the EU region, including data separation and approvals
• Defined three development stages through to partially autonomous management
• Designed role-specific views for business units, management and C-level
• Developed the business case and management pitch for the development stages
• Established an iterative response-quality validation process with the business unit
• Designed the operating model for assistance operations and initiated validation

Stack: Azure OpenAI, Azure AI Foundry, Snowflake, dbt, React, TypeScript, Entra ID, RAG, Agentic AI, analysis agents, Human-in-the-Loop, Prompt Engineering, LLM Evaluation, LLMOps, GDPR / EU region, Azure DevOps, Python, SQL, Change Management

• Owned requirements management for a connected mobile app integrating live vehicle hardware and embedded systems, from analysis through implementation (Requirements Management). App has grown to 500,000+ Google Play downloads and 5,800+ App Store ratings (4.4/5), ranking #170 in Germany's Navigation category.
• Steered digitalization and process optimization projects, coordinating between specialist departments, development teams, and external partners.
• Formulated requirements as user stories and acceptance criteria, accompanying implementation through testing and release.
• Applied genuine, practical AI Fluency to identify automation opportunities and accelerate delivery work. Applied SAFe and PRINCE2 methodologies; earned SAFe® 6 POPM and PRINCE2® Foundation certifications while in this role. Certified in Anthropic's AI Fluency framework.

• Own company for Interim Executive Manager assignments; Managing Director and sole shareholder Denis Dlouhy.
• Focus: transformation, post-merger integration, portfolio management, and HR for international corporations and hidden champions.

Responsible for the IT operations of a medium-sized mechanical engineering company (approximately 2 000 employees, annual revenue of approximately 400 million euros worldwide). Direct responsibility for 13 employees. At the same time, project manager for an internal carve-out (commercial and technical separation of the two business units worldwide).

Industry: Mechanical and plant engineering

Function: Director IT

• Responsibility for outsourced IT operations; provider management and service management.
• Responsibility for the complete separation of the two business units (applications, SAP R//3, Active Directory, IT infrastructure, ...); project planning and management; selection and management of service providers.
• TiSAX certification for one business unit; budget planning 2025 ff.
• Establishment and structuring of application operations, including the definition of operating models, SLAs/KPIs, and provider management in the SAP environment.
• Preparation of the operating organization for application operations of S/4 Hana (private cloud).