You will partner with TAMs, SAs, and service teams to provide customers with AWS AI/ML best practice guidance, diving deep into machine learning infrastructure services (PCS, ParallelCluster, HyperPod, Batch), promoting customers" AI/ML workloads to production, developing regional AI/ML strategies, advising on HPC-to-AI convergence patterns (simulation-surrogate loops, physics-informed neural networks), and training field teams on distributed training patterns, GPU/Trainium cluster operations, and the use cases and benefits of artificial intelligence and machine learning at scale. Architect and Validate Innovative Solutions - Design and implement production-grade AI/ML training and inference solutions leveraging Slurm-based job scheduling, distributed training frameworks (PyTorch FSDP, DDP, DeepSpeed, Megatron-LM), SageMaker HyperPod for managed GPU clusters with automated health checks and node replacement, high-performance parallel storage (Amazon FSx for Lustre), and container runtimes on Deep Learning AMIs (DLAMIs) against reference architectures and HPC lens to ensure performance, reliability, and cost governance at scale.