Senior Backend Engineer (m/f/d)

2 months ago

Munich, GermanySenior

Responsibilities

Design, build, and maintain backend services, REST APIs, domain models, and data access patterns for AI-enabled solutions.
Deliver scalable and resilient cloud-native microservices using Docker and Kubernetes.
Build and maintain CI/CD pipelines with automated testing, quality gates, and secure delivery practices.
Standardize API gateway exposure, including usage policies, throttling, authentication, authorization, and versioning.
Establish observability through dashboards, alerting, distributed tracing, runbooks, Azure Monitor, and Application Insights.
Diagnose complex issues across microservices, clusters, and pipelines and perform root-cause analysis with preventative improvements.
Implement security, resilience, secrets management, least-privilege access, container security, disaster recovery, auditability, and sensitive-data controls.
Collaborate with ML Engineers, Platform Engineers, AI Architects, and DevOps on shared foundations and engineering standards.

At least 5 years of professional backend engineering experience; MLOps or AI platform experience is a strong plus.
Expert-level Python experience, ideally with FastAPI, Pydantic, and SQLAlchemy or equivalent frameworks.
Strong software engineering fundamentals, including testing strategies, REST API versioning, documentation, code quality, and pragmatic system design.
Production experience with Docker and Kubernetes.
Strong CI/CD experience, preferably with GitHub Actions; ArgoCD or similar experience is also relevant.
Familiarity with Azure services including AKS, ACR, Key Vault, Azure Monitor, Application Insights, and Azure API Management.
Strong PostgreSQL experience including schema design, migrations, and performance tuning fundamentals.
Familiarity with distributed systems and event-driven architectures using Kafka.
Strong troubleshooting skills and an operational mindset.
Experience with MLOps patterns such as model packaging and deployment, batch versus real-time inference, feature pipelines, or experiment tracking is desirable.
Experience building internal libraries, platforms, or shared tooling used by multiple teams is desirable.
Experience in regulated environments requiring auditability and secure-by-default delivery is desirable.
Ability to work iteratively, communicate clearly, collaborate across global stakeholders, and adopt AI-assisted developer tools such as GitHub Copilot or Claude Code.

Professional development through a broad range of courses and targeted development programs.
Global environment with international mobility and career progression opportunities.
Work Well programs supporting health, wellbeing, and work-life balance.
Full-time, permanent employment.

10,000+ employees