Jobs · Engineering

Senior Tech Architect - PE

Quantiphi · United States · 1 wk ago
RemoteRemoteEngineeringFull-time

About the role

We are looking for a highly skilled Architect - Platform Engineer to design, optimize, and scale infrastructure for GenAI and LLM workloads. This role is ideal for someone with deep hands-on experience in GPU profiling, distributed training, and high-performance compute environments. You’ll play a key role in building out GenAI platform foundations, supporting production-grade deployments, and partnering closely with data science, MLOps, and application teams to bring cutting-edge AI solutions to life.

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 (CUDA, cuDNN, NCCL, Triton, RAPIDS, etc.)
  • Collaborate with cross-functional teams to deploy models in research and production environments
  • Build and support GenAI pipelines (fine-tuning, RAG, multi-modal inferencing, LLMOps)
  • Develop reusable infrastructure templates using tools like Terraform and Helm
  • Contribute to internal innovation (PoCs, workshops) and support client-facing delivery engagements

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 (CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT)
  • Strong foundation in Linux systems, performance tuning, and multi-GPU optimization
  • Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems)
  • Familiarity with Infrastructure-as-Code tools (Terraform, Ansible)
  • Experience with cloud GPU environments (GCP, Azure, AWS, OCI) and/or on-prem GPU clusters

Qualifications

  • 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 (Nice To Have):
    • Experience working with FHIR R4, HL7 v2, or SMART on FHIR
    • Integration with EHR systems (e.g., 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

Benefits

  • Make an impact at one of the world’s fastest-growing AI-first digital engineering companies
  • Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues
  • Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines
  • Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies
  • If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us

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