AI Infrastructure Principal Architect
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Overview
As the Principal AI Infrastructure Architect at Accenture, you set the technical direction for compute infrastructure that underpins large-scale AI/ML systems. You own the most complex architecture decisions across compute, networking, storage, orchestration, and model serving, guiding senior teams and shaping the roadmap. You prototype cost-optimized, scalable systems and establish reference architectures that scale across engagements. You translate trade-offs into business outcomes and steer technology strategy to deliver measurable value.
Responsabilità
- Set the overarching technical vision for compute infrastructure supporting large-scale AI/ML systems
- Own complex architecture decisions across compute, networking, storage, orchestration, and model serving
- Architect and prototype large-scale, cost-optimized compute and distributed training systems with reference implementations
- Define reference architectures, standards, and patterns and implement foundational tooling and automation
- Lead enterprise-scale architecture assessments and design reviews and validate findings in real environments
- Shape and steward the AI infrastructure roadmap, capacity planning, and technology evolution
- Identify and pilot promising emerging technologies and assess their fit in real conditions
- Drive performance and cost optimization of GPU/compute utilization and distributed workloads
- Serve as principal authority across hyperscaler cloud platforms with hands-on AI/ML knowledge
- Troubleshoot root causes across hardware, networking, software, and models and codify fixes
- Cultivate relationships with infrastructure partners and securing early access and credibility
- Provide executive and client-level technical advisory tying infrastructure trade-offs to business outcomes
- Define monitoring, observability, reliability strategy, SLAs, SLOs, and cost/performance governance
- Ensure security, compliance, and regulatory alignment of AI/ML infrastructure across solutions
- Mentor and grow the architect community through hands-on collaboration
- Champion cost-efficiency and value realization across the stack
Requisiti fondamentali
- Significant experience in coding, building, monitoring, and troubleshooting AI/ML applications and infrastructure
- Strong understanding of AI/ML concepts and computing infrastructure
- Proven programming experience (Python, Java, or C++)
- Experience with data pipelines/workflow tools (e.g., Apache Airflow, Kubeflow)
- Problem-solving skills and ability to work in a fast-paced environment
- Excellent communication and collaboration skills
- Extensive experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform
- Proven experience leading AI projects and teams
- Strong project management skills and ability to manage multiple projects
- Experience evaluating/selecting AI technologies and frameworks
- Ability to work with cross-functional teams and drive project alignment
- strong communication
- collaboration
- leadership
- AI/ML infrastructure
- compute optimization
- GPU/compute utilization
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