Job Summary

We are seeking a highly skilled AI Architect to design and implement AI-driven solutions for HP’s on-premises and cloud-based server and storage infrastructure. This role will focus on leveraging artificial intelligence and machine learning to improve productivity, increase uptime, and reduce overall spend across our infrastructure landscape. The ideal candidate will combine deep technical expertise with strategic vision to modernize HP’s infrastructure operations through automation, predictive analytics, and intelligent optimization.

Key Responsibilities

• Architecture & Design

  • Develop end-to-end AI architecture for server and storage environments (on-prem and cloud).
  • Define scalable, secure, and cost-efficient AI frameworks for infrastructure automation and optimization.
  • Select appropriate AI/ML technologies, tools, and platforms (e.g., Azure ML, AWS SageMaker, Kubernetes, Terraform).

• Implementation & Integration

  • Lead deployment of AI solutions for predictive maintenance, anomaly detection, and capacity planning.
  • Integrate AI models into existing IT workflows (e.g., monitoring, patching, ticket resolution).
  • Collaborate with infrastructure, storage, and cloud teams to ensure seamless integration.

• Optimization & Governance

  • Drive automation initiatives (Zero-Touch IT, AIOps) to reduce manual effort and improve reliability.
  • Implement cost optimization strategies using AI-driven insights for resource utilization and spend reduction.
  • Ensure compliance with HP’s security and governance standards.

• Collaboration & Leadership

  • Work closely with data scientists, DevOps, and business stakeholders to align AI initiatives with HP’s strategic goals.
  • Provide thought leadership on emerging AI technologies and infrastructure trends.
  • Mentor technical teams on AI best practices and architecture principles.

Required Qualifications

Preferred Skills

Impact of the Role

This position will play a critical role in modernizing HP’s infrastructure operations, enabling:

• Predictive maintenance to reduce downtime.
• Automated provisioning and patching for faster delivery.
• Cost savings through intelligent resource optimization.

Success Measures (first 12 months)

• ≥15% spend reduction across selected server/storage footprints through AI‑guided rightsizing and lifecycle policies.
• ≥20% decrease in manual tasks for provisioning/patching via ZTI/AIOps integrations.
• Productionizing 3–5 AI use cases with measurable reliability and cost KPIs.