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Sr GenAI Infra Specialist SA, AWS WWSO Startup

Amazon· Solutions Architecture / GTM Startup team (GenAI Infra)
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Hybrid (New York, NY), Hybrid (Herndon, VA), Hybrid (Seattle, WA)$169k - $228.6kFull-timePosted 4mo ago

About the role

Specialist Solutions Architect focusing on GenAI infrastructure for startup customers, specializing in training and inference optimization of large-scale AI models on AWS. Combines AI infrastructure architecture with model optimization to help customers adopt and scale GenAI workloads, working with startups, research labs, and enterprises.

Responsibilities

  • - Work directly with startup customers in GenAI model training and inference space to adopt and scale large-scale workloads on AWS
  • - Advise on AI infrastructure requirements and trade-offs (GPU/Trainium, cluster topology, storage, networking, cost optimization) for training and inference
  • - Provide deep technical guidance on inference optimization (self-managed on EKS, SageMaker endpoints, SageMaker Hyperpod Serving), batching, quantization, model parallelism, latency/throughput
  • - Provide deep technical guidance on training optimization (distributed training strategies, framework selection e.g., PyTorch/JAX/NeMo, SageMaker HyperPod, Slurm/PCS, checkpointing, data pipelines)
  • - Guide on GPU/accelerator profiling, bottleneck identification, optimizing utilization, system-level performance tuning
  • - Explain model optimization techniques (LoRA/QLoRA, RLHF/DPO, knowledge distillation, efficient serving techniques)
  • - Help GTM define growth assets, market sizing, opportunity pipeline, and technical content for field teams and thought leadership
  • - Develop demos, proof-of-concepts, reference architectures, and benchmarks to demonstrate AWS GenAI value
  • - Collaborate with product teams (EC2, Trainium/Inferentia, SageMaker, EKS, PCS, EC2) to shape product vision and features
  • - Work with account teams, researchers, ISVs, framework communities, and model providers to drive implementations and innovation

Qualifications

  • - 8+ years in technology domains (systems engineering, cloud infrastructure, HPC, ML/AI, distributed computing)
  • - 3+ years designing/implementing/consulting on large-scale AI/ML infrastructure with hands-on GPU-based computing, ML training infra, and inference serving systems

Skills

Required:Experience communicating complex technical concepts to technical and business audiencesGPU/accelerator optimization and profilingDistributed training and inference optimizationFrameworks (PyTorch, JAX, NeMo) and ML platforms (SageMaker, Slurm, PCS)

Benefits

  • Health insurance (medical, dental, vision) and prescription
  • 401(k) matching
  • Paid time off and parental leave
  • Comprehensive benefits package including life insurance, EAP, mental health support, flexible spending accounts, adoption and surrogacy reimbursement
  • Sign-on payments and RSUs
Last updated Oct 25, 2026. Interested? Apply on the company site.

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