Tech Architect - PE

Quantiphi

3d • Remote

About The Position

Quantiphi is seeking an Architect - Platform Engineering to design, optimize, and scale infrastructure for GenAI and LLM workloads. The role calls for hands-on expertise in GPU profiling, distributed training, and high-performance computing environments. The architect will help build GenAI platform foundations, support production-grade deployments, and partner with data science, MLOps, and application teams to deliver AI solutions. The position is remote in Canada or the United States and calls for 10+ years of experience.

Requirements

• 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, and Triton/TensorRT.
• Strong foundation in Linux systems, performance tuning, and multi-GPU optimization.
• Experience deploying GenAI workloads, including LLM fine-tuning, RAG pipelines, and multimodal systems.
• Familiarity with infrastructure-as-code tools such as Terraform and Ansible.
• Experience with cloud GPU environments (GCP, Azure, AWS, or OCI) and/or on-premises GPU clusters.

Nice To Haves

• 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.
• Comfort working in client-facing environments and collaborating with AI solution teams.
• Experience working with FHIR R4, HL7 v2, or SMART on FHIR.
• Integration experience with EHR systems such as Epic.
• Understanding of HIPAA compliance and healthcare data privacy.
• Exposure to clinical workflows, CDS Hooks, or patient-facing applications.
• Experience building clinical decision support systems or healthcare interoperability solutions.

Responsibilities

• 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, multimodal inferencing, and LLMOps.
• Develop reusable infrastructure templates using tools such as Terraform and Helm.
• Contribute to internal innovation through proof-of-concepts and workshops, and support client-facing delivery engagements.

Benefits

• Opportunity to make an impact at a fast-growing AI-first digital engineering company.
• Upskilling and opportunities to discover professional potential while solving complex technology challenges with colleagues.
• Work with disruptive innovators in a research-focused organization with 60+ patents filed across disciplines.
• Exposure to breakthrough AI, ML, data, and cloud technologies and Fortune 500 companies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed