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CoreWeave

Rents GPU cloud computing for AI developers

Solution Specialist - AI Runtime Services

Pre-Sales Solution EngineeringUpdated on Nov 13
Full-timeIn-person

About the Job

Requirements

  • 10+ years of experience in distributed systems, machine learning infrastructure, or production AI engineering, applying that expertise to drive customer outcomes and revenue.
  • 5+ years working with AI runtime systems, including model serving, inference optimization, containerized workload execution, or real-time machine learning pipelines, in a customer-facing or deal-shaping capacity.
  • Deep working knowledge of AI workload execution at runtime, including serving frameworks, batching strategies, GPU memory management, and performance factors that determine throughput and latency at scale; familiarity with vLLM, TensorRT-LLM, or Triton.
  • Experience with sandboxed and isolated execution environments, including microVM architectures, container runtimes, and secure multi-tenant scheduling, and understanding how execution isolation requirements affect platform selection.
  • Strong understanding of GPU memory hierarchies, model parallelism strategies, and how runtime architecture decisions affect cost, latency, and scalability for enterprise customers.
  • Familiarity with Kubernetes-native runtime orchestration, including autoscaling, scheduling policies, and GPU operators, and its impact on workload portability, operational complexity, and platform stickiness.
  • Ability to benchmark, explain, and commercially position runtime performance differences across deployment patterns, instance types, and serving configurations.

Responsibilities

  • Own the commercial and technical strategy for new customer wins in AI runtime infrastructure, where execution performance, deployment flexibility, and operational reliability are the primary buying triggers.
  • Drive new business opportunities where inference latency, throughput bottlenecks, workload isolation requirements, or operational complexity hinder scaling AI on CoreWeave.
  • Develop expertise across the AI runtime landscape, including model-serving architectures, execution scheduling, containerized AI workloads, and secure multi-tenant compute, using Inference and Sandboxes as flagship examples.
  • Translate customer requirements around serving frameworks such as vLLM, TensorRT-LLM, and TGI, batching strategies, and execution isolation into product feedback that shapes the AI Runtime Services roadmap.
  • Develop deal structures, technical playbooks, and benchmark narratives to help sales and solution architecture teams accelerate runtime-sensitive opportunities across AI deployment patterns.
  • Engage directly with enterprise and research buyers as the authoritative voice on runtime performance tradeoffs, cost-per-token economics, and architectural decisions for production-scale AI systems.
  • Design the commercial framework for large-scale runtime deployment deals, including throughput modeling, GPU utilization commitments, and service-level agreement structures.
  • Partner with product and infrastructure teams to maintain a competitive edge in serving efficiency, execution isolation, and operational reliability across active and prospective customer deployments.

Desired Qualifications

  • Experience driving new business or shaping product strategy in industries with high-throughput AI runtime demands, such as generative AI applications, autonomous systems, financial modeling, or developer platforms.
  • Prior background in technical sales, solution consulting, or product management supporting large-scale inference infrastructure or AI platform decisions.
  • Deep understanding of cost-per-token economics, inference fleet optimization, and the commercial tradeoffs between on-demand, reserved, and spot GPU capacity for runtime workloads.
  • An advanced degree in Computer Science, Machine Learning, or Engineering, or equivalent experience demonstrating the ability to operate at the intersection of technical architecture and commercial strategy.

About the Company

CoreWeave

Rents GPU cloud computing for AI developers

CoreWeave rents cloud computing to AI labs and businesses that train models and run them in production for research and commercial applications. Its platform combines NVIDIA graphics chips, storage, networking, and software built for demanding AI workloads across connected clusters scaled to fit each project. CoreWeave Forge connects tools for tracking experiments, testing models, and improving AI systems using feedback from production. Customers rent computing capacity through committed contracts or usage charges, while managed services handle the infrastructure needed to keep large workloads running. CoreWeave was founded in 2017 and is headquartered in Livingston, New Jersey.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Livingston, NJ
Founded
2017

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