A

Amazon

Sells products online and rents cloud computing

Senior Worldwide Specialist - AI Inference, Data & AI GTM

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 5 years of Go-To-Market, Business Development, Sales, or Consulting experience.
  • At least 5 years of experience working with Data & AI-related technologies, including AI/ML, Generative AI, Analytics, Database, and/or Storage.
  • Experience selling enterprise software or cloud-based applications.
  • Experience explaining complex technical concepts to business and technical audiences.
  • Experience presenting to technical and non-technical executive audiences.

Responsibilities

  • Define, build, and execute go-to-market initiatives to accelerate worldwide adoption of Amazon SageMaker AI, with a focus on Generative AI inference.
  • Use customer-engagement learnings to influence and drive service evolution and roadmap.
  • Work with AWS Generative AI Solution Architects, Product Managers, Marketing Managers, and geographically aligned field teams to run worldwide sales motions across industry segments and customer types.
  • Define sales motions, including customer segmentation and qualification, positioning quantitative and qualitative differentiators, and mechanisms and campaigns to accelerate sales cycles.
  • Execute sales motions through direct customer engagements and geographically aligned Data & AI specialists to prospect, develop pipeline, launch opportunities, and drive SageMaker AI usage and revenue.
  • Help customers understand AI inference workloads and use cases, emerging open-source technologies, native product capabilities for cost and performance optimization at scale, model cost and total cost of ownership, and savings from inference optimization techniques.
  • Demonstrate the ease of use of AI inference in SageMaker, discuss the service roadmap, and handle objections from AWS teams and customers.
  • Secure customer quotes, nurture public references, and help Marketing develop case studies.
  • Synthesize insights from customer engagements to help prioritize the service roadmap and influence service evolution.
  • Use prospect propensity lists and work with field teams to secure meetings with customer stakeholders.
  • Conduct consultative customer calls, demonstrate offering differentiators, discuss pricing and savings packages, gather feedback on SageMaker AI use, and secure workshops, proofs of value, or proofs of concept.
  • Encourage current customers to provide public quotes or references, or to co-present in webinars or at AWS events.
  • Develop and update sales-motion assets, and conduct enablement sessions to teach field teams how to execute sales motions.
  • Conduct customer-facing webinars to raise awareness of SageMaker Inference.
  • Collect customer-backed product feedback and participate in roadmap-prioritization sessions.
  • Document customer and market insights for the team and leadership.

Desired Qualifications

  • At least 5 years of highly technical pre-sales experience at B2B companies, such as enterprises, startups, or system integration services companies, preferably in machine learning and/or artificial intelligence; subject-matter expertise in cluster-based computing frameworks such as Kubernetes and Ray.
  • Experience building sales plays and playbooks; prospecting, advancing, and closing technical sales pipeline to drive adoption of machine-learning or artificial-intelligence products and services focused on model inference; and teaching account teams how to sell technical products and services.
  • Experience structuring and running benchmark initiatives, documenting optimization strategies, building total-cost-of-ownership and pricing models, and demonstrating cost/performance differentiation to customers.
  • Experience advocating for customers by understanding pain points, helping them navigate cost/performance/quality trade-offs in cluster-based computing systems at scale, and conveying insights to product teams.
  • Experience managing multiple initiatives and campaigns simultaneously, including customer engagements, sales motions, webinars, and sales-asset development, across Product, Marketing, Solution Architects, and Account teams.
  • Experience managing, tracking, and communicating customer and market insights, objective business metrics, and risks.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

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