Job Summary
Job Summary: We are seeking an experienced Solutions Architect with deep expertise in AI/ML infrastructure, High Performance Computing (HPC), and container platforms to join our dynamic team focused on delivering HPE Private Cloud AI and Enterprise AI Factory Solutions. This role is instrumental in architecting, deploying, and optimizing private cloud environments that leverage HPE’s co-developed solutions with NVIDIA, as well as validated HPE reference architectures, to support enterprise-grade AI workloads at scale. \r\n\r\n \r\n\r\nThe ideal candidate will bring strong technical expertise in AI infrastructure, container orchestration platforms, and hybrid cloud environments, and will play a key role in delivering scalable, secure, and high-performance AI platform solutions powered by HPE GreenLake and NVIDIA AI Enterprise technologies. Job Description: Primary Skills: HPC & AI Infrastructure, Containerization & Orchestration, Operating Systems & Virtualization, Cloud, DevOps & MLOps \\\\r\\\\n\\\\r\\\\nSecondary Skills: Networking & Protocols, Programming & Automation, Soft Skills & Leadership.Job Responsibilities : Leadership and Strategy: \r\n\r\nProvide delivery assurance and serve as the lead design authority to ensure seamless execution of Enterprise grade container platform —including Red Hat OpenShift and SUSE Rancher, HPE Private Cloud AI and HPC/AI solutions, fully aligned with customer AI/ML strategies and business objectives. \r\n\r\nAlign solution architecture with NVIDIA Enterprise AI Factory design principles, including modular scalability, GPU optimization, and hybrid cloud orchestration. \r\n\r\nOversee planning, risk management, and stakeholder alignment throughout the project lifecycle to ensure successful outcomes. \r\n\r\nSolution Planning and Design: \r\n\r\nArchitect and optimize end-to-end solutions across container orchestration and HPC workload management domains, leveraging platforms such as Red Hat OpenShift, SUSE Rancher, and/or workload schedulers like Slurm and Altair PBS Pro. \r\n\r\nEnsure seamless integration of container and AI platforms with the broader software ecosystem, including NVIDIA AI Enterprise, as well as open-source DevOps, AI/ML tools, and frameworks. \r\n\r\nOpportunity assessment: \r\n\r\nLead technical responses to RFPs, RFIs, and customer inquiries, ensuring alignment with business and technical requirements. \r\n\r\nConduct proof-of-concept (PoC) engagements to validate solution feasibility, performance, and integration within customer environments. \r\n\r\nAssess customer infrastructure and workloads to recommend optimal configurations using validated reference architectures from HPE and strategic partners such as Red Hat, NVIDIA, SUSE, along with components from the open-source ecosystem. \r\n\r\nInnovation and Research: \r\n\r\nStay current with emerging technologies, industry trends, and best practices across HPC, Kubernetes, container platforms, hybrid cloud, and security to inform solution design and innovation. \r\n\r\nCustomer-centric mindset: \r\n\r\nAct as a trusted advisor to enterprise customers, ensuring alignment of AI solutions with business goals. \r\n\r\nTranslate complex technical concepts into value propositions for stakeholders \r\n\r\nTeam Collaboration: \r\n\r\nCollaborate with cross-functional teams, including subject matter experts in infrastructure components—such as HPE servers, storage, networking—and data science teams to ensure cohesive and integrated solution delivery. \r\n\r\nMentor technical consultants and contribute to internal knowledge sharing through tech talks and innovation forums.
Key Responsibilities
2. Lead The Support Team In Understanding Client Requirements And Ensure That Service Delivery Aligns With Client Expectations By Utilizing Azure Kubernetes For Scalable Application Deployment.
3. Mentor And Guide Project Team Members, Fostering Transparent Communication Of Project Goals Using Infrastructure As Code (Iac) Principles With Terraform In Azure Environments.
4. Introduce Innovative Ideas And Process Improvements, Leveraging Windows Azure Paas Capabilities To Enhance Organizational Efficiency And Operational Effectiveness.
5. Provide Tailored Solutions In Line With Customer Needs By Analyzing Operational Environments And Utilizing Azure Iaas And Iac Technologies To Drive Tangible Business Results.
Skill Requirements
Skill Requirement : 8–10 years of hands-on experience in architecting and implementing HPC, AI/ML, and container platform solutions within hybrid or private cloud environments, with a strong focus on scalability, performance, and enterprise integration. \r\n\r\n.
1. In-Depth Knowledge Of Azure Iaas And Iac Practices.
2. Solid Experience With Azure Kubernetes For Application Management.
3. Proficiency In Using Terraform For Infrastructure Automation.
4. Familiarity With Windows Azure Paas Services For Application Development And Deployment.
5. Strong Problem-Solving And Team Leadership Skills.
Other Requirements
Other Requirement : Bachelor’s/master’s degree in computer science, Information Technology, or a related field. \r\n\r\nProfessional certifications in AI Infrastructure, Containers and Kubernetes are highly desirable —such as RHCSA, RHCE, CNCF certifications (CKA, CKAD, CKS), NVIDIA-Certified Associate - AI Infrastructure and Operations.