GCP Platform Architecture

Quantiphi; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Healthcare benefits

Professional growth opportunities

Job summary

Quantiphi is seeking an Architect - Platform Engineer to design, optimize, and scale GenAI infrastructure for multi-GPU workloads. The role emphasizes GPU profiling, distributed training, and high-performance compute environments.

You will collaborate with data science, MLOps, and application teams to deploy cutting-edge AI solutions. Responsibilities include implementing scalable LLM and GenAI pipelines, managing Slurm clusters, and delivering reusable IaC templates using Terraform and Helm.

Qualifications

• Experience with Slurm-based clusters or distributed training environments.
• Deep knowledge of container orchestration (Kubernetes/OpenShift) in production.
• Strong Linux systems background and multi-GPU performance tuning.
• Hands-on experience deploying GenAI workloads (LLMs, RAG, fine-tuning).
• Familiarity with IaC tools (Terraform, Ansible) and cloud GPU platforms.

Responsibilities

• Design scalable GenAI infrastructure for multi-GPU workloads.
• Profile, benchmark, and optimize GPU performance for distributed training.
• Manage compute scheduling with Slurm and container platforms (Kubernetes/OpenShift).
• Develop reusable infrastructure templates (Terraform, Helm) for GenAI deployments.
• Collaborate with data science and MLOps teams to deploy models in prod.

Skills

Distributed training

Multi-GPU optimization

GenAI workloads

Linux performance tuning

NVIDIA GPU ecosystem

Cloud GPU environments

MLOps collaboration

Education

Bachelor's degree in CS/EE or related field

Tools

Slurm

OpenShift

Kubernetes

Terraform

Ansible

NVIDIA CUDA

NCCL

TensorRT

Job description

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.

Key Responsibilities:

• Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU
• Perform GPU profiling, benchmarking, and performance optimization for distributed training
• Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes
• 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

Basic Qualifications:

• 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

Other Qualifications (OQs):

• 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

What’s in it for YOU at Quantiphi:

• 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.