Job Description
Role Description:
Architect and build custom Artificial Intelligence (AI) infrastructure solutions leveraging the client Kubernetes Platform and AI. You will be responsible for designing high-performance computational stacks that integrate AI, high-speed software-defined storage, and GPU-accelerated nodes. Your mission is to make AI infrastructure "invisible" by optimizing for performance, power consumption, and seamless hybrid-multicloud scalability across on-prem.
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Summary
As an AI Infrastructure Engineer, you will design tailored AI solutions that bridge the gap between private data centers and public cloud. Your day-to-day will involve optimizing the client computational stack for large language models (LLMs) and generative AI workloads. You will serve as the SME for AI, ensuring that compute, storage (client Objects/Files), and networking (Flow) are perfectly tuned for AI model training and inference.
Responsibilities
- Hybrid Multicloud Architecture: Design seamless AI workflows using NC2 on Prem, allowing for rapid bursting of AI workloads from on-prem AHV clusters to the public cloud.
- Data Services for AI: Architect high-performance storage backends using Objects (S3-compatible) to handle the massive datasets required for AI/ML.
- Kubernetes & Orchestration: Deploy and manage AI workloads using client Kubernetes Platform to ensure containerized AI models are scalable and resilient.
- Infrastructure-as-Code: Implement IaC using Calm or Terraform to automate the lifecycle of GPU-enabled nodes.
- Observability: Design frameworks (monitoring, logging, alerting) for proactive issue detection. Hands on experience on Prometheus, Grafana, ELK, and OpenTelemetry.
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- Ensure high availability, disaster recovery, and fault tolerance across all systems.
- Networking & Security: Familiarity with Zero-Trust architectures, enterprise networking, storage, and virtualization.
- Invisible Infrastructure: Modernize legacy 3-tier AI silos into a unified, web-scale environment.
Professional & Technical Skills
- Core: Deep proficiency in AOS (Acropolis Operating System) and AHV (Native Hypervisor).
- AI Performance: Experience with GPU Passthrough and vGPU configurations to optimize AI training performance.
- Security: Applying work Flow for micro segmentation to secure sensitive AI training data.
- Cost Management: Using Cloud Manager (NCM) Cost Governance to monitor and optimize spend across hybrid environments.
Experience: 3-5 Years .
The expected compensation for this role ranges from $45,000 to $121,000 .
Final compensation will depend on various factors, including your geographical location, minimum wage obligations, skills, and relevant experience. Based on the position, the role is also eligible for Wipro's standard benefits including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options.
Applicants are advised that employment in some roles may be conditioned on successful completion of a post-offer drug screening, subject to applicable state law.
Wipro provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Applications from veterans and people with disabilities are explicitly welcome.
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