3 days ago
Kronberg, GermanyStaff+
Responsibilities
- Set the technical vision and strategy for compute infrastructure supporting large-scale AI/ML systems.
- Own architecture decisions across compute, networking, storage, orchestration, and model serving.
- Architect and prototype large-scale distributed training systems, reference implementations, proofs of concept, and benchmarks.
- Define reference architectures, standards, architectural patterns, infrastructure-as-code, and automation.
- Lead enterprise architecture assessments, design reviews, workload profiling, and optimization efforts.
- Plan AI infrastructure capacity, scaling, technology evolution, and roadmaps.
- Pilot emerging technologies and evaluate their suitability for production solutions.
- Optimize GPU and compute utilization, distributed training, model-serving workloads, performance, and cost.
- Provide technical authority across hyperscaler platforms and AI/ML infrastructure services.
- Troubleshoot complex hardware, networking, software, and model issues and codify solutions.
- Cultivate infrastructure-partner relationships and represent the practice in partner forums.
- Advise executives and clients on infrastructure trade-offs and business outcomes.
- Define and implement monitoring, observability, reliability, SLA, SLO, and cost/performance governance strategies.
- Ensure enterprise integration, security, compliance, and regulatory alignment.
- Mentor and develop senior and lead architects through pairing, design collaboration, and reviews.
- Lead and manage AI projects and teams while coordinating cross-functional alignment.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related engineering field.
- Significant experience coding, building, monitoring, and troubleshooting AI/ML model applications and designing infrastructure for on-premises or public-cloud deployment.
- Experience in the cybersecurity industry.
- Considerable experience in AI/ML infrastructure engineering or related hyperscaler-platform roles deploying large-scale solutions.
- Strong understanding of artificial intelligence, machine learning, computing infrastructure, and preferably AI infrastructure.
- Proficiency in Python, Java, or C++.
- Experience with data-pipeline and workflow-management tools such as Apache Airflow and Kubeflow.
- Proven experience leading and managing AI projects and teams.
- Strong project-management, problem-solving, communication, collaboration, and cross-functional alignment skills.
- Demonstrated experience evaluating and selecting AI technologies and frameworks.
- German language proficiency at a minimum B2 level.
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.