Note: The job is a remote job and is open to candidates in USA. Quantiphi is an AI-first global digital engineering company that helps organizations transform complex challenges into measurable business impact. The Architect - Platform Engineer will design, optimize, and scale infrastructure for GenAI and LLM workloads, including GPU profiling, distributed training, high-performance computing, cloud platforms, and production-grade AI deployments. The role also involves developing automation, infrastructure-as-code, Kubernetes platforms, CI/CD processes, and providing technical leadership in client engagements.
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
- Develop and deliver automation software required for building & improving the functionality, reliability, availability, and manageability of applications and cloud platforms
- Champion and drive the adoption of Infrastructure as Code (IaC) practices and mindset
- Design, architect, and build self-service, self-healing, synthetic monitoring and alerting platform and tools
- Automate the development and test automation processes through CI/CD pipeline (Git, Jenkins, SonarQube, Artifactory, Docker containers)
- Build container hosting-platform using Kubernetes
- Introduce new cloud technologies, tools; processes to keep innovating in the commerce area to drive greater business value
- Lead the technical discussion regarding architecture designing and troubleshooting with the clients and provide solutions proactively as required
Skills
- * 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
- * Serve as a mentor or guide for senior resources / team leads
- * Lead the technical discussion regarding architecture design
- * 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
- * Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers
- * 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
- Remote work in the US East/Canada region
- Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
- Up-skill 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.
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