Senior Platform Engineer

Scaleyo; Deutschland; Hybrid; EUR 60,000 - 100,000; Full time

Job summary

Crateflow, a fast-growing AI startup, seeks a backend/platform engineer with 3+ years on Azure to own scalable services and pipelines. You will containerize workloads with Docker, deploy on AKS, and drive CI/CD with Terraform/Bicep while enabling MLflow-based MLOps.

Collaboration with data scientists and a strong English/German mindset are essential. The role offers hybrid work, a competitive salary, and opportunities to shape the product and technology stack in a data-driven, founder-style

Qualifications

• 3+ years in backend or platform engineering on Azure.
• Strong expertise in Kubernetes, Docker and container orchestration.
• Proven experience with CI/CD and Infrastructure-as-Code frameworks.
• Proficient in Python; familiarity with Django or FastAPI.
• Solid knowledge of ML libraries (LightGBM, CatBoost, XGBoost, NeuralForecast) and MLflow.
• Hands-on experience with data ingestion and workflow tools (Airflow, Prefect).
• Track record with monitoring stacks (Prometheus, Grafana).
• Self-driven approach, clear communication in English or German.
• Founder mentality and hands-on attitude in a startup setting.

Responsibilities

• Design and implement scalable backend services (Python, Django REST).
• Containerize workloads with Docker and deploy on Kubernetes (AKS).
• Build and maintain CI/CD pipelines (GitHub Actions or Azure DevOps) and Infrastructure-as-Code (Terraform / Bicep).
• Develop MLOps workflows for time-series forecasting models with MLflow tracking.
• Automate data ingestion pipelines using Prefect or Airflow to replace ad-hoc scripts.
• Offload training and inference tasks to background workers or Azure Functions.
• Implement robust monitoring and alerting (Prometheus, Grafana, Azure Monitor).
• Collaborate with data scientists on distributed model training across large datasets.

Skills

Azure

Kubernetes

Docker

Python

Django

CI/CD

Terraform

MLflow

Airflow

Prefect

Prometheus

Grafana

English

German

Founder mentality

Tools

Docker

Kubernetes

GitHub Actions

Azure DevOps

Terraform

Bicep

AKS

MLflow

Airflow

Prefect

Prometheus

Grafana

Job description

About Crateflow

Crateflow is a fast-growing AI startup on a mission to revolutionize inventory management and the S&OP process with data-driven decision intelligence. Our end-to-end AI platform runs on Azure, serving retailers and manufacturers worldwide. We seek a highly driven engineer who thrives in a startup environment, takes full ownership of their work and embraces a founder mentality to drive our product forward.

What You’ll Do

• Design and implement scalable backend services (Python, Django REST)
• Containerize workloads with Docker and deploy on Kubernetes (AKS)
• Build and maintain CI/CD pipelines (GitHub Actions or Azure DevOps) and Infrastructure-as-Code (Terraform / Bicep)
• Develop MLOps workflows for time-series forecasting models with MLflow tracking
• Automate data ingestion pipelines using Prefect or Airflow to replace ad-hoc scripts
• Offload training and inference tasks to background workers or Azure Functions
• Implement robust monitoring and alerting (Prometheus, Grafana, Azure Monitor)
• Collaborate with data scientists on distributed model training across large datasets

Requirements

What We’re Looking For

• 3+ years in backend or platform engineering on Azure
• Strong expertise in Kubernetes, Docker and container orchestration
• Proven experience with CI/CD and Infrastructure-as-Code frameworks
• Proficient in Python; familiarity with Django or FastAPI
• Solid knowledge of ML libraries (LightGBM, CatBoost, XGBoost, NeuralForecast) and MLflow
• Hands-on experience with data ingestion and workflow tools (Airflow, Prefect)
• Track record with monitoring stacks (Prometheus, Grafana)
• Self-driven approach, clear communication in English or German
• Founder mentality and hands-on attitude in a startup setting

Bonus Skills

• Experience with Polars for high-performance data processing
• Background in Spark, Ray or Dask for distributed compute
• Familiarity with feature stores and model registries (Feast, MLflow)
• Frontend experience with React and TypeScript served via Nginx
• Understanding of secret management solutions (Vault, Azure Key Vault)

How We Work

• Decisions are lightweight, fast feedback loops
• Founder-style ownership and autonomous execution
• Hybrid work with regular off-sites

What We Offer

• Competitive salary (€60,000–€100,000) depending on your skillset
• You shape the product, the stack, and the outcomes
• High leverage environment with fast data-driven decision making“