AI Platform Engineer

Jobtailor; München; Vor Ort; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Jobtailor in München is seeking an AI Platform Engineer to drive the architecture of our AI-driven platform. You will design and operate backend services and APIs, enabling data scientists and developers to build, deploy, and scale applications.

The role requires hands-on experience with Python or Go, Docker, Kubernetes, Terraform, and AWS, plus familiarity with FastAPI and modern JS for internal tools. You will collaborate across teams to accelerate AI initiatives.

Qualifikationen

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• Proven experience as Software Engineer, Platform Engineer, or AI/MLOps Engineer with strong software development background.
• Strong proficiency in Python or Go with production-grade applications.
• Experience designing and building APIs and backend services, ideally with FastAPI.
• Solid understanding of AI/ML concepts, particularly LLMs, RAG, and vector databases.
• Hands-on experience with Docker and Kubernetes.
• Experience with Infrastructure as Code (Terraform) and cloud platforms (preferably AWS).
• Familiarity with modern JavaScript/TypeScript and a UI framework (React, Vue) for internal tools is a plus.

Aufgaben

• Architect and build scalable AI platform components and APIs.
• Develop end-to-end platform enabling rapid development, deployment and scaling.
• Create backend services, internal tools, and automated workflows.
• Build core platform services, manage ML lifecycle.
• Develop data ingestion for vector and graph databases.
• Create full-stack tooling and dashboards for developers, data scientists and managers.
• Own application and model lifecycle, ensuring production performance.
• Collaborate with software and data science teams to gather platform requirements.

Kenntnisse

Python

Go

API Design

Backend Development

AI/ML concepts

LLMs

Software Architecture

Ausbildung

Bachelor's degree in Computer Science, Engineering or related field

Tools

Docker

Kubernetes

Terraform

AWS

FastAPI

React

TypeScript

Jobbeschreibung

Responsibilities

• As an AI Platform Engineer, you will be a key architect of the software and systems that empower our AI-driven initiatives.
• More than just managing infrastructure, you will be actively building the cohesive, end-to-end platform that enables our teams to develop, deploy, and scale applications rapidly.
• You will engineer robust backend services, create internal tools, and design the automated workflows that form the foundation of our AI capabilities.
• Develop Core Platform Services: Design, build, and operate the backend services and APIs that serve our AI models and manage the ML lifecycle.
• Develop the Data Ingestion Platform: Design, build, and maintain the services and automated workflows responsible for populating our vector and graph databases, ensuring our AI applications have access to timely and accurate data.
• Build Full-Stack Tooling: Create user-facing tools and internal dashboards that allow developers, data scientists and managers to interact with the AI platform.
• Own the Application & Model Lifecycle: Implement and maintain the core platform components and ensure the performance of production systems.
• Collaborate and Enable: Work closely with software and data science teams to understand their needs, gather requirements for the platform, and provide the tools and support that accelerate their work.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Proven experience as a Software Engineer, Platform Engineer, or an AI/MLOps Engineer with a strong software development background.
• Strong proficiency in Python or Go, with a track record of building scalable, production-grade applications.
• Experience designing and building APIs and backend services, ideally with frameworks like FastAPI.
• A solid understanding of AI/ML concepts, particularly Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.
• Hands‑on experience with Docker and Kubernetes for containerization and orchestration.
• Experience with Infrastructure as Code (e.g., Terraform) and cloud platforms (preferably AWS).
• Familiarity with modern JavaScript/TypeScript and a UI framework (e.g., React, Vue) for building internal tools is a significant plus.