Experienced AI/ML-Ops Engineer

Beschreibung

Job Zusammenfassung In dieser Rolle architektierst und wartest du eine zentrale AI-Plattform mit Vertex AI, entwickelst automatisierte CI/CD-Pipelines und implementierst Sicherheitsframeworks für LLMs, um datenschutzkonforme AI-Lösungen zu gewährleisten. Job Zusammenfassung In dieser Rolle architektierst und wartest du eine zentrale AI-Plattform mit Vertex AI, entwickelst automatisierte CI/CD-Pipelines und implementierst Sicherheitsframeworks für LLMs, um datenschutzkonforme AI-Lösungen zu gewährleisten. Deine Rolle im Team AI Platform Engineering: Architect and maintain a centralized AI platform using Vertex AI, GKE, and BigQuery, ensuring it serves as a robust foundation for company-wide AI initiatives. Automated Guardrails & Governance: Design and implement automated safety layers (guardrails) to ensure LLM security, data privacy, and compliance with the EU AI Act. Self-Service Tooling: Build and maintain agentic tooling frameworks and "golden paths" that allow internal tech teams to deploy AI agents and RAG systems independently. AI / ML-Ops & CI/CD Pipelines: Develop end-to-end automated pipelines (CI/CD/CT) for model training, testing, deployment, and versioning of AI agents. Monitoring & Anomaly Detection: Implement advanced observability solutions to monitor model performance, detect drift, and identify system anomalies in real-time. Internal Tech Consulting: Act as a technical subject matter expert, advising product and engineering teams on how to architect, integrate, and scale AI solutions within the platform ecosystem. Unsere Erwartungen an dich Qualifikationen Agentic AI Frameworks: Practical knowledge of frameworks like LangChain, LangGraph, Google Agent Development Kit (ADK), and an understanding of how to operationalize agentic workflows at scale. Governance & Security: Familiarity with AI safety tools (e.g., NeMo Guardrails) and a mindset for building "secure by design" and compliant AI systems. Analytical Mindset: Proven ability to build monitoring for non-deterministic systems, focusing on anomaly detection and performance metrics. Communication: Excellent English skills with the ability to translate complex infrastructural requirements into clear documentation and guidance for other developers. Erfahrung Experience: 3-5+ years in Software Engineering or DevOps, with a clear specialization in ML/AI Ops and cloud-scale infrastructure. GCP Expertise: Deep hands-on experience with Google Cloud Platform, specifically Vertex AI (Model Registry, Pipelines, Model Monitoring) and BigQuery. Technical Stack: Strong proficiency in Python and Infrastructure-as-Code (e.g., Terraform). Experience with Kubernetes (GKE) and Docker. Benefits Work-Life-Integration ⏰ Flexible Arbeitszeiten 🏠 Home Office Mehr Netto 🛍 Mitarbeitervergünstigungen Gesundheit, Fitness & Fun 🚲 Jobrad Themen mit denen du dich im Job beschäftigst Machine Learning Cloud Computing AI Metadaten Level: Erfahren Job Feld: IT, Data, DevOps Anstellung: Vollzeit Vertragsart: Unbefristetes Dienstverhältnis Arbeitsmodell: Hybrid, Onsite Unternehmenstyp: Etablierte Firma Branche: Elektronik, Automatisation, Internet, IT, Telekom Ort: Ingolstadt | Deutschland

Tech Stack