Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms
Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.
We are also proud to be certified as a Great Place to Work, reflecting our commitment to our people and our culture.
For more details, visit: Website or Linkedin Page
Role: Senior - Platform Engineer
Experience Level: 5+ yrs
Work Location: East/Canada [ET & CT]
Role Overview
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 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
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.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
