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- Develop cloud-based solutions to grow the GenAI business
- Enable new capabilities for customers to develop and deploy GenAI workloads on AWS
- Foster the enablement of AWS technical community, solution architects, and sales teams
- Technical and business background to drive engagement and interact at high levels
- Deep familiarity across the stack – compute infrastructure, ML frameworks, orchestration layers, parallel computing, MLOPs, and target use cases in the cloud
- Passion for helping companies/partners understand best practices for operating on AWS
- Bachelor's degree in computer science, engineering, mathematics or equivalent
- 8+ years of technology domain areas experience (software development, cloud computing, systems engineering, etc.)
- 3+ years of design, implementation, or consulting in applications and infrastructures experience
- 5+ years building or optimizing computational applications for large scale HPC systems
- Understanding of deep learning training and inference workloads and requirements
- 5+ years of infrastructure architecture, database architecture, and networking experience
- Experience working with end user or developer communities
- Professional experience in deep learning training and inference workloads
Worldwide Specialist Solutions Architect - Houston - Amazon

Description
Define the Future of Go to Market (GTM) at AWS with Generative AI
AWS Sales, Marketing, and Global Services (SMGS) drives revenue, adoption, and growth from small- and mid-market accounts to enterprise-level customers.
You will be part of the core worldwide GenAI, Training & Inference team, responsible for defining, building, and deploying targeted strategies to accelerate customer adoption of our services and solutions across industry verticals.
You will work directly with important customers in the GenAI model training and inference space, helping them adopt and scale large-scale workloads on AWS. You will conduct model performance evaluations, optimizations, and work directly with engineering and product to optimize the ML stack for efficiency and scale. External/internal evangelism, demos, and proof-of-concepts are also responsibilities.
Key Responsibilities:
Requirements:
Basic Qualifications:
Preferred Qualifications:
Amazon is an equal opportunity employer and does not discriminate based on protected veteran status, disability, or other legally protected status.
This position requires a strong sense of ownership, drive, and scrappiness, as well as the ability to learn, optimize, and build new technologies and techniques.
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