AI Engineer designing and deploying enterprise - scale AI systems in the Innovation team of Client Data & Analytics platform. Driving innovation through Generative AI solutions while ensuring security and governance standards.
About the role
- AI Architect focusing on designing and implementing AI-driven solutions for HP’s on-premises and cloud environments. Collaborating with teams to modernize infrastructure operations and improve productivity.
Responsibilities
- 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).
- 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.
- 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.
- 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.
Requirements
- Bachelor’s/Master’s in Computer Science, Data Science, or related field.
- 7+ years in infrastructure architecture/operations; 3+ years architecting enterprise AI/ML solutions.
- Hands‑on expertise with: AI/ML : Azure ML, AWS SageMaker, Python (PyTorch/TensorFlow), feature/store design.
- Automation/MLOps : GitHub Actions/Azure DevOps, Terraform/Ansible, model monitoring, drift detection.
- Platforms : Kubernetes, containers, microservices, event streaming (Kafka).
- Observability : Prometheus/Grafana/Datadog/Splunk; log/metric/trace correlation for AIOps.
- Strong grasp of AIOps , predictive analytics, reliability engineering, and infrastructure‑as‑code.
- Experience with compliance frameworks (SOX/ITGC) and enterprise security controls.
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Long term/short term disability insurance
- Employee assistance program
- Flexible spending account
- Life insurance
- Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure
- 11 paid holidays
- Additional flexible paid vacation and sick leave
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