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Design, optimize, and scale multi-GPU infrastructure for GenAI/LLM workloads. Perform GPU profiling and benchmarking, manage Slurm and Kubernetes/OpenShift clusters, enable NVIDIA GPU stack, build GenAI pipelines (fine-tuning, RAG, multi-modal), create IaC templates, and support production deployments and client engagements.

The Senior Data Engineer will build and maintain data ingestion pipelines, manage FHIR serialization, and work within a spec-driven development framework, ensuring operational stability and high data quality for healthcare data workloads.

Lead organizational change management for cloud migration: conduct impact analyses, develop strategic communications, design and deliver training and enablement, engage stakeholders, assess readiness, define adoption metrics, and report progress to program leadership.

Lead and manage large-scale, multi-pillar cloud transformation programs using SAFe. Own PI planning, program cadence, risk and dependency management, stakeholder communication, and coaching of Scrum Masters. Support backlog organization, change management, and Jira/Confluence administration to ensure value delivery.

Architect and implement enterprise-grade MLOps/LLMOps on AWS (EKS-first), building scalable pipelines for training, validation, registry, deployment, monitoring, CI/CD, observability, lineage and governance; serve as technical authority, conduct architecture reviews, troubleshoot systems, and mentor engineering teams across projects.

Lead and facilitate Scrum ceremonies, coach teams on agile practices, coordinate migrations with application owners, manage risks and dependencies, maintain Jira artifacts and sprint reporting to enable predictable delivery.

Lead strategic cloud migration planning and stakeholder discussions; assess on-prem VMware environments; define target cloud architectures and governance; design cloud network and security (Palo Alto); oversee hands-on migration of VMs and complex workloads to ROSA/AWS/Azure/GCP; implement containerization and OpenShift migration strategies.

Serve as the primary client contact and lead discovery, translate requirements, and oversee end-to-end delivery of ML, software, and data analytics professional services. Define scope, manage budgets and resources, mitigate risks, ensure reporting, and collaborate with architects and talent teams to match skills to client needs.

Design and scale GenAI/LLM infrastructure for multi-GPU environments, perform GPU profiling and optimization, manage Slurm/OpenShift/Kubernetes clusters, enable NVIDIA GPU stack, build GenAI pipelines and IaC templates, and support production deployments and client engagements.

Design, build, and optimize scalable infrastructure for GenAI/LLM workloads across multi-GPU environments. Perform GPU profiling and distributed training optimization, manage Slurm and Kubernetes/OpenShift clusters, enable NVIDIA GPU stack, create IaC templates (Terraform/Helm), and collaborate with data science and MLOps teams to deploy production GenAI pipelines.