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
Plan & document backend architecture in the Arc42 framework
Extend & communicate the domain model using DDD principles
Manage and extend application infrastructure on Azure with Pulumi

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)

Hands-on ownership of a real AI product used by enterprise customers
Work directly alongside the founding team from day one
Hybrid work model: Munich North, minimum one day per week in the office, otherwise flexible (open to strong candidates elsewhere in the EU for the right fit); onboarding will take in-office
A steep learning curve at the intersection of LLM engineering, enterprise GRC, and startup operations
The chance to shape the AI team as we grow

Application Architect – AI Native Startup

Key skills