Senior Python Engineer - AI-Driven Backend & APIs

Springtime Technologies; Wien; On-site; EUR 47,000 - 56,000; Full time

Benefits offered by this job

Brand exposure

Flexible working

Impactful engineering

AI momentum role

Job summary

Springtime Technologies is hiring senior Automation engineers to build the services behind Invoicetrack's automation and data capabilities. You will design, build, and operate backend Python services, APIs and data models, while guiding architectural decisions and AI integration.

Expect ownership, leadership potential, and collaboration with product management. The role emphasizes scalable architecture, clean code, and production-grade deployment using Docker and Kubernetes.

Qualifications

• 5+ years of Python production experience.
• Experience integrating LLM APIs (OpenAI, Claude, Azure OpenAI) into production.
• Strong RESTful API design and distributed systems experience.
• Familiarity with Docker and Kubernetes in production environments.
• Excellent English communication skills.

Responsibilities

• Design and build Python services with RESTful APIs from design to production.
• Lead back-end architecture and data modelling decisions with clean architecture.
• Integrate LLM APIs and AI/ML components into production services.
• Establish coding standards and provide feedback through code reviews and discussions.
• Turn product problems into technical solutions with the product manager.
• Ship via CI/CD pipelines, build Docker images, deploy to Kubernetes.
• Grow the team by sharing knowledge and helping hire new engineers.

Skills

Python

AI/ML integration

REST APIs

Distributed systems

CI/CD

Docker

Kubernetes

Team collaboration

Ownership

Technical leadership

SaaS

React

TypeScript

English communication

Tools

GitHub Copilot

Claude

Azure OpenAI

Job description

Springtime Technologies is hiring senior Automation engineers to build the services behind Invoicetrack's automation and data capabilities. You will design, build, and operate backend Python services, APIs and data models, while guiding architectural decisions and AI integration.

Expect ownership, leadership potential, and collaboration with product management. The role emphasizes scalable architecture, clean code, and production-grade deployment using Docker and Kubernetes.