Enterprise Integration Architect connecting Kinaxis Maestro supply - chain software with complex enterprise ecosystems. Defining SAP, API, cloud, data, and integration architectures for global customers.
About the role
- Platform Architect scaling GPU infrastructure for GenAI and LLM workloads at Quantiphi, an AI-first digital engineering company. Optimizing distributed training, Kubernetes clusters, and production AI deployments.
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, 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
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