Sr. Worldwide Specialist Solutions Architect - HPC/ML, Computer Aided Engineering (CAE), Weather & GPU Computing

About the role

The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), responsible for driving revenue, adoption, and growth from large and fast-growing small- and mid-market accounts to enterprise-level customers including public sector.

Responsibilities

• Collaborate with the wider AWS teams to help customers and partners architect HPC Solutions that leverage AWS Services.
• Engage with Solution Architects, Account Managers, Professional Services, and Partners to define an HPC Engagement strategy for AWS operational territories and key accounts, with emphasis on public sector National Super Computing Centers, Government agencies, and/or AI/ML, CAE, Weather and accelerated computing with GPU.
• Provide thought leadership on solutions that benefit customers through the use of AWS Services, contributing to external publications and internal training.
• Serve as a key member of the business development and accounting management team to ensure customer success in building and migrating applications, software, and services on the AWS platform.
• Assist solution providers with the definition and implementation of technical and business strategies.
• Capture and share best-practice knowledge amongst the worldwide AWS solution architect community.

Requirements

Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients.

Bachelor's degree.

Deep HPC experience for workloads in a domain such as CAE, Weather Simulation, oil and gas, automotive / aerospace, financial services or pharmaceuticals.

Experience in architecting an HPC system and infrastructure with orchestration schedulers (e.g. Slurm, Torque, Symphony or GridServer), parallel file systems (Lustre, IBM Spectrum Scale).

Experience in deployment, tuning, benchmarking and management of HPC technologies in a multi-user environment.

Deep GPU knowledge in HPC and/or AI/ML frameworks.

Qualifications

• Advanced degree in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields.
• Experience in a customer-facing role, engaging with customer executives, technologists or partners to solve business problems with advanced technologies.
• Working knowledge of HPC schedulers and distributed/parallel file systems, underlying IT systems, and the HPC development process, high throughput and tight coupling approaches.
• Working knowledge of containers such as Docker, Kubernetes, Singularity.
• Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external stakeholders.