AI Platform Engineer – Developer, Product Enablement

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking an experienced engineer to own the lifecycle of internal AI APIs, SDKs, and developer tooling, integrating AI capabilities into existing workflows. You will build CI/CD–integrated AI systems, design evaluation and testing pipelines, and establish engineering standards for AI development.

The role focuses on Python-based backend work, production-quality AI/ML systems, and observability to ensure reliable AI outputs in a fast-paced environment.

Qualifikationen

• 5+ years in software engineering, platform engineering, or infrastructure.
• At least 2 years building production AI/ML systems.
• Strong Python and backend development skills.

Aufgaben

• Own the lifecycle of internal AI APIs, SDKs, and developer tooling to abstract LLM complexity.
• Build and maintain CI/CD-integrated AI systems including code review automation and test generation pipelines.
• Drive product development acceleration by integrating AI capabilities into workflows.
• Design evaluation frameworks and automated testing pipelines for AI system outputs.
• Build observability tooling to monitor model behavior, token costs, latency, and production output quality.
• Establish shared prompt libraries and reusable context management systems.
• Define and enforce engineering standards for AI system development.
• Provide technical guidance and conduct architectural reviews of AI features.

Kenntnisse

Python

Backend development

AI/ML production systems

Software engineering

CI/CD

Tools

Terraform

LLM APIs

Jobbeschreibung

Responsibilities

• Own the lifecycle of internal AI APIs, SDKs, and developer tooling to abstract LLM complexity
• Build and maintain CI/CD-integrated AI systems including code review automation and test generation pipelines
• Drive product development acceleration by integrating AI capabilities directly into existing collaborative workflows
• Design evaluation frameworks and automated testing pipelines to ensure quality of AI system outputs
• Build observability tooling to monitor model behavior, token costs, latency, and production output quality
• Establish shared prompt libraries and reusable context management systems
• Define and enforce engineering standards for AI system development
• Provide technical guidance and conduct architectural reviews of AI features

Requirements

• 5+ years in software engineering, platform engineering, or infrastructure, with at least 2 years building production AI/ML systems
• Deep experience with LLM APIs and strong understanding of system behavior under real production load
• Experience building internal developer platforms, tooling, or shared infrastructure
• Proficiency in Python and at least one compiled language; comfortable across the full backend stack
• Preferred: Familiarity with agentic frameworks, RAG architectures, vector databases, or infrastructure-as-code (Terraform)

Core Competencies

Demonstrates expertise in building and maintaining AI systems, with a strong focus on LLM APIs, CI/CD integration, and automated testing frameworks. Proficient in Python and backend development, with a solid understanding of production AI/ML system behavior and engineering standards.