Architecture must turn into code
When the team does not need another slide deck but sound decisions and someone who helps build the critical parts.
For companies, consultancies, and intermediaries
Senior software architecture and engineering – amplified by AI.
Elton Marku works as part of an existing product or engineering team. He combines more than 15 years of enterprise experience with an agent-assisted working model that accelerates analysis and implementation without removing responsibility from the team.
Software Architect · Lead Full-Stack Engineer · AI-enabled Engineering
Expected availability: from January 2027
One counterpart for architecture, code, and technical decisions.
15+Years in architecture and engineering
End-to-endFrom architecture to production
Frankfurt · RemoteEngagement model by agreement
// when the engagement fits
Seniority where system context and implementation meet.
The greatest leverage comes not as an isolated reviewer but on the critical path of a real initiative.
An established system must evolve
When legacy, regulation, data flows, and live operations have to be considered together.
AI must fit the engineering workflow
When agents and LLMs should be used productively without leaving quality, privacy, and traceability to chance.
// contribution to the team
Technical leadership that still ships.
Architecture and system design
System boundaries, integration patterns, and technical decisions become concrete enough for the team to act on.
- Event-driven architecture
- APIs and data models
- Cloud and platform
- ADRs and trade-offs
Hands-on lead engineering
Critical paths are not delegated. Architecture is validated through implementation, reviews, and production integration.
- Java and Spring Boot
- Angular and TypeScript
- Kafka
- Kubernetes and CI/CD
AI-enabled delivery
AI agents increase throughput and analytical breadth. Their use is adapted to security constraints, the codebase, and team process.
- Codebase analysis
- Agent workflows
- Test and review support
- LLM integration
// ai within the project team
No AI theatre – a controlled engineering advantage.
The models and tools used depend on the client's security and data constraints. The benefit comes from connecting agents with system context and senior review.
- Structured analysis of large codebases and dependencies
- Preparation and implementation of clearly bounded changes
- Extension of tests, documentation, and migration paths
- Reviews against architecture decisions and acceptance criteria
No unchecked changes, no invented certainty, and no model access to sensitive data without an agreed framework.
// project contexts
Enterprise experience that project partners can place.
Selected engagements across regulated and business-critical system landscapes. The complete project profile can be shared in a concrete placement process.
- DZ Bank
- Deutsche Post
- Deutsche Bahn
- LBB
- VisualVest
- Amadeus
- T-Systems
Does the profile fit your project?
Describe the role, system context, timeframe, and engagement model. You will receive a clear answer on whether and how Entwicklerherz can support you.