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# Application Architect - AI Native Startup

- **Company:** Auxilius
- **Location:** München, Germany
- **Contract:** Temporary contract
- **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Amazon Web Services, Applications Architecture, Automation of Tests, Microsoft Azure, Continuous Integration, Software Design Patterns, DevOps, IntelliJ IDEA, Software Deployment, Spring-boot, Cloudformation, Solid Principles, Bicep, Terraform, Domain Driven Design, Domain Model
- **Published:** July 22, 2026
- **Apply:** https://www.adzuna.de/details/5802983960

## About the Role

* You are comfortable with architecture principles and practices, including:
 * C4 modelling
 * Arc42 framework
 * Design patterns
 * You are highly experienced in TDD and/or BDD
 * You are opinionated and passionate about good design
 * Experience with Domain Driven Design (DDD)
 * Deep experience with Java and Spring Boot
 * A strong DevOps mindset (the DevOps Handbook is your bible) and experience building:
 * reliable CI/CD pipelines and release processes
 * production-grade monitoring/observability and incident response practices
 * continuous improvement loops (post-incident reviews, operational learning, and prioritizing reliability work)
 * Experience leading and enabling development teams

Absolute must-haves

 * SOLID principles & clean code
 * TDD
 * IntelliJ power-user
 * Claude Code (or comparable AI-assisted development workflows)
 * Azure or AWS infrastructure-as-code (e.g., Terraform, Bicep, or CloudFormation)

## Description

As an Application Architect (m/f/d), you will be one of the first full-time senior engineers and collaborate closely with our Co-Founder and CTO. You will own the backend architecture and help the team scale quality and delivery speed.

In the first 6-12 months you will have:

 * established a clear target architecture and documentation baseline using Arc42
 * clarified and communicated the core domain model using DDD principles
 * introduced/standardized an AI-driven development process, from feature specs to production deployment
 * strengthened engineering practices via coaching, pairing, and feedback loops (especially for junior developers)
 * improved reliability and delivery through better CI/CD, test automation, and infrastructure hygiene

Responsibilities

 * Collaborate with the team to find strong solutions to new types of problems in an AI-first architecture
 * Drive a DevOps-style approach across the full specification * development * delivery lifecycle (inspired by the DevOps Handbook)
 * Propose and implement approaches to make delivery faster and more reliable (e.g., improving flow, feedback loops, and recovery)
 * Implement and evolve monitoring/observability across systems (metrics, logs, traces, alerting) so we can detect issues early and learn from production
 * Coach and collaborate with junior developers on good development, design and architecture practices
 * Collaborate with the team to develop an AI-driven development process from feature specs down to production deployment


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