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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