Tobias Diehl

Backend Engineer · Java/Kotlin · Spring Boot · Cloud

I build backend systems with stable APIsclear data modelsrobust integrationsreliable delivery

Portrait of Tobias Diehl

I am a Cloud Backend Developer at Cosee, building domain-oriented backend systems with Java/Kotlin, Spring Boot, PostgreSQL, AWS and reliable delivery. In cross-functional Scrum teams I clarify requirements, work closely through pairing and reviews, and share knowledge so solutions remain sustainable for the team.

About me

About me and how I work

Backend implementation, domain clarification and delivery belong together. Good software comes from shared decisions, stable system boundaries and reliable communication with product, stakeholders and teammates.

Ownership

I take features from requirements through API and data model to tests, delivery and observability.

Team impact

In the team, I share knowledge through code reviews, pair programming and technical coaching so decisions become shared.

Product orientation

I shape requirements with stakeholders so technical options stay understandable and realistic to evaluate.

Technical focus

Backend engineering is the core. Architecture, delivery, teamwork and product understanding are the areas where I create value beyond writing code.

Backend

Java/Kotlin, Spring Boot, REST APIs, data models, tests, authentication, validation and clean interfaces.

KotlinJavaSpring BootRESTPostgreSQLTesting

Architecture

Domain-driven design, hexagonal architecture, OpenAPI, integration boundaries, domain modules and maintainable structures.

Domain-driven DesignHexagonal ArchitectureOpenAPIIntegration

Delivery

AWS, Docker, Terraform, CI/CD, Kubernetes/Helm, Caddy, monitoring and the connection between development and operations.

AWSTerraformDockerGitLab CIMonitoringKubernetes

Product & Stakeholders

Feature planning, Scrum, pair programming, client workshops, technical clarification, LLM-assisted development workflows, product-owner-adjacent responsibility and personal apps, games and product ideas.

Feature PlanningStakeholdersProduct ThinkingLLM WorkflowsSwiftUIGame AI

Practical working skills

Beyond stack and tools, these are the skills that turn requirements into stable software in a team.

Scalable backend architectures

Domain modules, robust interfaces and clear system boundaries.

Requirements analysis and user stories

Clarifying, prioritizing and translating requirements into deliverable backend work.

LLM-assisted development workflows

Using AI tools deliberately for research, review, tests and iteration.

Continuous delivery and CI/CD

Pipelines, containers and release flows for repeatable delivery.

Scrum and cross-functional teams

Collaboration with product, design, QA and stakeholders in clear Scrum routines.

Monitoring and production analysis

Runtime signals, logs and failure patterns for stable operations.

Clean code and clean architecture

Code that keeps domain logic testable, understandable and easy to evolve.

Unit, integration and contract tests

Tests where domain rules and interfaces need protection.

Pair programming and technical coaching

Sharing knowledge, explaining decisions and strengthening backend and testing practices.

Stakeholder coordination

Explaining technical options clearly and supporting product decisions.

Tech-Talk

Tech talk: AWS Cloud Quest to AI Engineer?

Tech talk with Patrick Wolf about AWS Cloud Quest, the Generative AI role and whether game-based cloud training works as practical technical learning.

Open on YouTube

Professional Experience

Professional experience

I have worked at Cosee on backend and cloud topics since 09/2020, and since 01/2025 full-time as a Cloud Backend Developer. My work connects backend services, cloud delivery, architecture, Scrum routines and product-facing coordination across client projects.

View work projects

Contact

Contact and CV

If my profile fits a backend, platform or product-adjacent engineering role, reach me by email, phone or LinkedIn. I am interested in roles where backend depth, teamwork and product closeness come together.