Senior Tech Architect – PE

🕒 August 16

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🏛️ Architect

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 14%

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Quantiphi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Series A on 2019-12

Consulting • Healthcare • Logistics

Quantiphi is a leading AI-first digital engineering company that leverages a decade of industry expertise to empower businesses through scalable, secure, and adaptable AI solutions. By integrating cutting-edge technology with real-world applications, Quantiphi transforms organizations across various sectors including healthcare, finance, education, and retail. Their services span AI applications, data analytics, cloud infrastructure modernization, and custom AI implementations. Quantiphi partners with technology giants like AWS, Google Cloud, NVIDIA, and others to drive AI adoption and deliver transformational opportunities for enterprises.

📋 Description

• Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU environments • Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads • Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments • Enable and optimize the NVIDIA GPU stack, including CUDA, cuDNN, NCCL, Triton, and RAPIDS • Collaborate with cross-functional teams to deploy models in research and production environments • Build and support GenAI pipelines, including fine-tuning, RAG, multi-modal inferencing, and LLMOps • Develop reusable infrastructure templates using Terraform and Helm • Contribute to internal innovation through PoCs and workshops • Support client-facing delivery engagements

🎯 Requirements

• 10+ years of experience • Strong experience with Slurm and distributed training environments • Hands-on expertise with Red Hat OpenShift and/or Kubernetes • Deep knowledge of the NVIDIA GPU ecosystem, including CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT • Strong foundation in Linux systems, performance tuning, and multi-GPU optimization • Experience deploying GenAI workloads, including LLM fine-tuning, RAG pipelines, and multi-modal systems • Familiarity with Infrastructure-as-Code tools such as Terraform and Ansible • Experience with cloud GPU environments including GCP, Azure, AWS, OCI and/or on-prem GPU clusters • Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers • Knowledge of LLMOps frameworks and MLOps integration • Familiarity with vector databases and retrieval systems for RAG architectures • Comfortable working in client-facing environments and collaborating with AI solution teams • Healthcare domain experience is nice to have: FHIR R4, HL7 v2, SMART on FHIR, EHR systems such as Epic, HIPAA compliance, clinical workflows, CDS Hooks, patient-facing applications, clinical decision support systems, or healthcare interoperability solutions

🏖️ Benefits

• Upskill and discover your potential through complex challenges in cutting-edge technology • Work in a research-focused organization with 60+ patents filed • Exposure to AI, ML, data, and cloud technologies • Gain exposure working with Fortune 500 companies • Opportunities to learn, grow, and interact with colleagues from varied experience and backgrounds around the globe • Diverse and hybrid work culture