Sr. GTM Specialist AI Infrastructure - Israel, WWSO EMEA Advanced Compute
Amazon
- Location
- IL, Tel Aviv
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Posted
- 52d ago
Skills
About this role
Join AWS' newly formed AI Infrastructure team to lead the go-to-market strategy for one of the fastest-growing segments in cloud computing for Israel. You will work with the most innovative AI companies in the region—from foundation model builders to enterprises deploying state-of-the art inference and training workloads—helping them run and train Open Weight, Finetuned, Bespoke, and Domain Specific Large Language Models best on AWS. AWS is establishing dedicated AI Infrastructure teams across EMEA to capture the rapidly expanding market for AI training, inference, and accelerated compute. As the Business Development Manager for AI Infrastructure in Israel, you will own the regional GTM strategy, drive revenue growth, and build deep customer relationships with organizations pushing the boundaries of AI—model producers, domain-specific AI builders, startups, ISVs, and enterprises scaling AI-native applications. This is a greenfield opportunity to shape a new function within a high-growth domain. You will be part of an EMEA-wide team of AI Infrastructure specialists, working at the intersection of GPU-accelerated computing, large-scale model training, inference optimization, and cloud infrastructure. The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. We work backwards from our customers’ most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam. The WWSO AI Infrastructure team is the go-to partner that delivers the architecture, deployment, and optimization guidance required for self-managed workloads. The ideal candidate must be self-motivated with a proven track record of customer obsession and delivering results. The ability to connect technology with measurable business value is critical. You should also have a demonstrated ability to think strategically about business, products, and technical challenges in AI. Key job responsibilities - Own and execute the AI Infrastructure go-to-market strategy for Israel, driving pipeline creation, deal progression, and revenue attainment across EC2 accelerated compute, Amazon EKS for AI workloads, and Amazon SageMaker HyperPod and Inference - Identify, engage, and win high-value AI infrastructure customers—including model producers, AI-native startups, and enterprises building domain-specific AI solutions across industries such as financial services, healthcare, manufacturing, and telecommunications - Develop and execute account-level strategies for priority customers running or evaluating large-scale AI training and inference workloads, positioning AWS as the platform of choice - Execute strategic partner co-sell motions with key ecosystem players including NVIDIA, open-weight model providers (e.g. Meta, Mistral), and inference framework communities (vLLM, Ray, Anyscale) - Collaborate with consulting and systems integration partners to enable AI infrastructure best practices and drive joint customer engagements - Lead scaled GTM motions including developer community engagement, customer roundtables, workload assessments, and regional campaigns that position AWS AI infrastructure leadership - Aggregate voice-of-customer feedback on capacity, performance, pricing, and feature requirements—working with AWS service teams to influence product roadmaps and