Hands-on technical leadership for software teams under change.
I join product teams as a Technical Lead or Solutions Architect to modernise architecture, improve delivery reliability, and introduce AI workflows that remain reviewable and owned by the team.
Inside the work. Sharper delivery. AI with judgment.
Available from September 2026 · 2–5 days/week · German and English
20+ years in software delivery20 client engagements
Verified enterprise outcomes
Retail · Düsseldorf
Jan 2024 – Jul 2026
Role progression
- React Expert
- Technical Lead
- Solutions Architect
I was engaged as React Expert to modernise the POS software that runs on every cash register in more than 1,200 Douglas stores across 14 European countries.
Personal ownership
- extended the solution into C#/.NET and personally designed and shipped the unified API, applying architecture patterns across stacks and using AI tooling as part of a reviewable engineering workflow
- developed and maintained a production CRM backend in TypeScript/Node.js with NestJS and Express, covering API endpoints, configuration, and external service integrations
Team delivery and contribution
- onboarded 1 senior and 2 junior developers; all productive contributors within weeks
- introduced "Full Stack Fridays", team-driven learning sessions covering Figma prototyping, GraphQL, C#/.NET, and more
Bring me in when
typical starting points
A critical modernisation is losing momentum
The architecture is becoming harder to change, business logic is duplicated, releases are risky, or the team is trapped between old and new systems.
Strategy is not surviving contact with delivery
Leadership intent is clear in meetings, but ownership, priorities, planning, reviews, and technical decisions pull in different directions.
AI experiments need to become dependable work
The team has tools or pilots, but lacks governed access, useful context, review points, repeatable workflows, or clear ownership.
How I help
architecture · leadership · ai workflows
Most engagements combine two of these. The mix follows the problem in front of the team, not a fixed package.
Architecture and safer change
I clarify boundaries and ownership, reduce duplicated business logic, improve testability, observability, and recovery, and make releases and future changes safer.
Embedded technical leadership
I make decisions with the team, align architecture, product priorities, and delivery, mentor engineers and improve review quality, and keep leadership intent connected to implementation.
AI-enabled engineering workflows
I identify work that benefits from assistants or agents, connect tools to approved systems with controlled access, add deterministic checks and human review, and build practices the team can understand and own.
Ways to work together
three shapes / one conversation
Cadence and duration are agreed per engagement and depend on current availability.
Embedded Technical Lead or Solutions Architect
3–5 days per week · typically 3–9 months
- Hands-on architecture and implementation
- Team leadership, mentoring, and delivery improvement
- Best for modernisation, integration, or recovery work
Architecture and Delivery Assessment
usually 5–10 working days
- Interviews, code and architecture review, delivery-system review
- Prioritised findings and practical next steps
- Optional implementation follow-through
AI-enabled Engineering Advisory
usually 1 day per week or a fixed-scope package
- Use-case selection, workflow design, access and review model
- Agent or assistant prototypes where appropriate
- Team enablement and governance close to actual delivery
How I work
working style / what stays behind
- Embedded closely enough to understand the actual constraints.
- Direct with sponsors and respectful of the people doing the work.
- Hands-on with architecture, code, reviews, and delivery.
- Pragmatic about Agile and AI: use what improves the system, discard what does not.
- Focused on leaving clearer ownership and stronger capability behind.
No transformation theatre, detached slideware, or AI adoption for its own sake.
Questions I get asked
ai, hands-on, cadence, location
How do you use AI in client work?
Only within the client's approved security and data-handling constraints. I separate client environments, control tool access, keep important actions reviewable, and use deterministic checks around model output. AI supports engineering judgment; it does not replace accountability.
Are you still hands-on?
Yes. The work includes architecture, code, reviews, debugging, delivery practices, mentoring, and stakeholder alignment. I am most useful where technical decisions and team execution need to improve together.
Do you work part-time?
Yes. Embedded engagements can be structured from two to five days per week when responsibilities, meeting cadence, and response expectations are explicit.
Do you work onsite?
I am based in Munich and work remotely across DACH, with planned onsite work where it materially improves the engagement.
Engagement log
context over logo wall
Let's talk
direct / capacity-aware / one inbox
Send a short description of the team, the system, and what needs to change. You get a direct answer about fit, not a pitch.