亚马逊Specialist BD, AI/ML/GenAI, SSO/GenAI Team

Engage in Senior-level customer meetings to drive AWS AI/ML/GenAI adoption. Diving into customer’s business challenges and executing strategies on how the AWS AI/ML/GenAI services can help address and resolve these challenges. Serve as an evangelist for the AWS AI/ML/GenAI products within AWS and externally. Define, build and deploy enterprise focused sales and business development campaigns around the AWS AI/ML/GenAI offering. -Engage, support and scale business development and sales teams across AWS to be capable of delivering the AWS AI/ML/GenAI value proposition to customers and partners. Develop a standard market intelligence framework and dynamic analytic model to be utilized by the AWS Sales, Business Development and Marketing teams. Bring the various stakeholders together to help build collective mindshare in augmenting the AWS AI/ML/GenAI products. Establish mechanisms to measure and track metrics related to adoption of the AWS AI/ML/GenAI products, and execute improvements to the approach based on those measurements. Prepare and deliver business reviews to the senior management regarding the AWS AI/ML/GenAI business.

• Sales & Revenue Contribution: o Support the achievement of sales targets by developing and maintaining a healthy pipeline and guiding customers through end-to-end sales cycles, from discovery through to agreement; o Create detailed account plans and territory strategies in partnership with internal teams, while maintaining accurate forecasting using CRM tools; o Collaborate with customers to identify and qualify high-impact AI use cases aligned to their business priorities and strategic objectives. • Sales & Solution Advisory o Act as a trusted advisor on AWS AI services, helping customers understand potential outcomes, value, and return on investment; o Lead technical discovery sessions and contribute to demonstrations, proofs of concept, and solution design, including model selection, fine-tuning, and deployment approaches; o Provide guidance on model evaluation, responsible AI practices, governance considerations, and relevant compliance requirements. • Customer Engagement & Market Development o Build and maintain strong relationships with decision-makers and executive stakeholders through a consultative, collaborative approach; o Partner with internal teams to deliver workshops, enablement sessions, and solution reviews that support customer learning and adoption; o Share customer insights and feedback with AWS AI product teams to help inform product direction and improvements.

-Engage in Senior-level customer meetings to drive AWS AI/ML/GenAI adoption. Diving into customer’s business challenges and executing strategies on how the AWS AI/ML/GenAI services can help address and resolve these challenges. -Serve as an evangelist for the AWS AI/ML/GenAI products within AWS and externally. -Define, build and deploy enterprise focused sales and business development campaigns around the AWS AI/ML offering. -Engage, support and scale business development and sales teams across AWS to be capable of delivering the AWS AI/ML value proposition to customers and partners. -Develop a standard market intelligence framework and dynamic analytic model to be utilized by the AWS Sales, Business Development and Marketing teams. -Bring the various stakeholders together to help build collective mindshare in augmenting the AWS AI/ML products. -Establish mechanisms to measure and track metrics related to adoption of the AWS AI/ML products, and execute improvements to the approach based on those measurements. -Prepare and deliver business reviews to the senior management regarding the AWS AI/ML business.

- Drive EC2 Graviton adoption for strategic customers by conducting performance benchmarking (Redis, MySQL, MongoDB, Kafka, Cassandra), resolving ARM64 compatibility issues, and delivering migration plans that achieve 20-40% price-performance improvement - Design and deliver Agentic AI on K8S(EKS) solutions — including Kata/Firecracker isolation, Karpenter auto-scaling, Graviton-first architecture, and enterprise security hardening — for customers building AI agent infrastructure - Deliver customer-facing workshops that generate production pipeline and EC2 Graviton revenue pull-through - Support EKS platform engineering for large-scale customers — Karpenter optimization, Spot instance diversification, observability, and cost visibility - Collaborate with EC2/EKS service teams on PFRs, capacity planning, and instance selection guidance for emerging workload patterns (Agentic AI, HPC, crypto/Web3) A day in the life You start the day reviewing a customer's Graviton benchmark results — MongoDB on M8g shows 39% improvement over M7i, exceeding their 20% target. Mid-morning, you join a customer workshop helping 60+ engineers deploy Agentic AI workload on EKS. After lunch, you troubleshoot by implementing instance diversification. Late afternoon, you prepare a Graviton5 preview proposal for a strategic account. Your work directly converts into customer cost savings and new AWS revenue.