Data Center Architect

What success looks like in this role:

DC Architect is responsible for designing implementing and optimizing modern data center infrastructures. This role requires expertise in data center networking cloud integration highperformance computing and AIdriven automation. The architect will ensure high availability scalability security and efficiency of data center operations leveraging the latest AI technologies for automation predictive maintenance and energy efficiency.

• Provides Solutions Architecture consultation and advice Unisyswide.

• Works with clients Product Owners Sales & Sales Excellence teams and other stakeholders to align the architectural direction of solution intent.

• Serves as lead on largescale solution and component development engaging with crossfunctional leaders and stakeholders to ensure mutual understanding ongoing communication and alignment of outcome expectations.

• Conducts or leads studies to determine the economic technical and organizational feasibility of proposed solutions.

Key Responsibilities:

1. Data Center Architecture & Design:

• Design and develop scalable resilient and highperformance data center architectures.

• Define and implement data center topology including compute storage networking and virtualization.

• Ensure seamless integration of onpremises and cloudbased (hybrid/multicloud) infrastructures.

• Develop AIdriven optimization models for workload balancing power efficiency and predictive scaling.

2. Implementation & Deployment:

• Oversee the deployment of data center infrastructure including servers storage SDN and hyperconverged infrastructure (HCI).

• Implement AIpowered automation tools for resource provisioning capacity planning and selfhealing systems.

• Integrate GPUbased computing for AI/ML workloads supporting AIdriven applications and deep learning frameworks.

• Work closely with crossfunctional teams to deploy secure highperformance solutions.

3. Network & Security Architecture:

• Design and implement AIoptimized networking for highspeed lowlatency data transfers.

• Configure SDN NFV and intentbased networking (IBN) solutions for data center automation.

• Implement AIdriven security solutions including anomaly detection threat prediction and automated response systems.

4. AI & Automation in Data Centers:

• Utilize AI for predictive analytics in infrastructure health monitoring and fault prediction.

• Deploy AIpowered DCIM (Data Center Infrastructure Management) solutions for automated energy optimization.

• Implement AIOps (Artificial Intelligence for IT Operations) to improve performance monitoring and troubleshooting.

• Optimize edge computing and AI workloads within data centers for faster processing and realtime analytics.

5. Cloud & Hybrid Infrastructure:

• Design cloudnative architectures ensuring seamless hybrid cloud and multicloud integration.

• Optimize workloads between onprem edge and cloud environments using AIbased orchestration.

• Implement containerized infrastructure with Kubernetes OpenShift and cloudbased AI solutions.

6. Performance Optimization & Sustainability:

• Improve energy efficiency using AIpowered cooling and power management systems.

• Ensure high availability and disaster recovery using AIassisted fault tolerance and failover mechanisms.

• Work on Green Data Center initiatives to reduce carbon footprint using AIdriven insights.

#LISP2

You will be successful in this role if you have:

• BA/BS degree and 12 years relevant experience OR equivalent combination of education and experience

• Masters degree preferred and proven skills in

• Data Center Design: Expertise in hyperconverged infrastructure (HCI) SDN SDWAN and highperformance computing (HPC).

• Networking & Security: Deep knowledge of BGP EVPN VXLAN firewall security Zero Trust and microsegmentation.

• AI & Automation: Handson experience with AIdriven network and data center automation tools (e.g. NVIDIA AI Enterprise Ansible Terraform AIdriven DCIM).

• Cloud & Virtualization: Experience with VMware OpenStack Kubernetes AWS/GCP/Azure networking.

• AI/ML in Data Centers: Knowledge of AI frameworks like TensorFlow PyTorch and AI hardware (NVIDIA GPUs TPUs).

• Monitoring & Optimization: Experience with AIOps predictive analytics and intelligent workload management.

Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age blood type caste citizenship color disability family medical history family status ethnicity gender gender expression gender identity genetic information marital status national origin parental status pregnancy race religion sex sexual orientation transgender status veteran status or any other category protected by law.

This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers. If you are a US job seeker unable to review the job opportunities herein or cannot otherwise complete your expression of interest without additional assistance and would like to discuss a request for reasonable accommodation please contact our Global Recruiting organization at or alternatively Toll Free:(Prompt 4. US job seekers can find more information about Unisys EEO commitment here.