AI Infra Architect — Flexible, Hands-on, Production-Ready

Accenture DACH; Wien; Hybrid; EUR 48.000 - 59.000; Vollzeit

Benefits dieser Stelle

Flexible working models

Home office

Training opportunities and certs

Zusammenfassung

Accenture is seeking a Hands-on AI Infrastructure Architect in Vienna to design and optimize AI/ML infrastructure, including GPU clusters and distributed training environments. You will architect, deploy, and monitor AI systems, build data pipelines, and contribute to security and governance across InfraOps and MLOps.

A strong coding background and mentoring are essential. You will collaborate with senior architects, lead workstreams, and drive architecture decisions while leveraging container

Qualifikationen

• Bachelor's degree in CS/Engineering or related field.
• Hands-on experience in coding, monitoring, and troubleshooting AI/ML infrastructure.
• Strong understanding of AI/ML and computing infrastructure.
• Proficiency in Python, Java, or C++.
• Experience with data pipelines/tools like Airflow, Kubeflow.

Aufgaben

• Write, review, and debug code and infrastructure-as-code for AI infra.
• Provision compute resources across cloud and on-premises, incl. GPU clusters.
• Design and maintain CI/CD pipelines forAI systems and models.
• Deploy AI systems and data pipelines into production.
• Lead container orchestration using Docker/Kubernetes and model serving.
• Mentor junior engineers and lead code reviews.
• Document architecture standards and security best practices.

Kenntnisse

Strong problem solving

Excellent communication

Mentoring

Team collaboration

Adaptability

Ausbildung

Bachelor's degree in Computer Science/Engineering

Tools

Docker

Kubernetes

CI/CD

Apache Airflow

Kubeflow

Jobbeschreibung

Accenture is seeking a Hands-on AI Infrastructure Architect in Vienna to design and optimize AI/ML infrastructure, including GPU clusters and distributed training environments. You will architect, deploy, and monitor AI systems, build data pipelines, and contribute to security and governance across InfraOps and MLOps.

A strong coding background and mentoring are essential. You will collaborate with senior architects, lead workstreams, and drive architecture decisions while leveraging container