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Senior Storage Solutions Architect

4 weeks ago


Toronto, Ontario, Canada Amazon Web Services Canada, Inc. - D46 Full time
About the Role

We are seeking a highly skilled Storage Solutions Architect to join our team at Amazon Web Services Canada, Inc. - D46. As a key member of our team, you will be responsible for designing and implementing storage solutions that meet the needs of our customers.

Key Responsibilities
  • Thought Leadership – Evangelize AWS Storage services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
  • Partner with SAs, Sales, Business Development, Data and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements.
  • Act as a technical liaison between customers and the AWS Storage services teams to provide customer driven product improvement feedback.
  • Develop and support an AWS internal community of Data and AI related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.
  • Candidate Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers and with the academic community.
Requirements
  • 7 years of design, implementation, or consulting in applications and infrastructures experience
  • 5+ years management of technical, customer facing resources
  • 5 years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
Preferred Qualifications
  • 5+ years of infrastructure architecture, database architecture and networking experience
  • Experience working with end user or developer communities
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team
  • Active in the open source community, such as HuggingFace, StableDiffusion, etc
  • Large models pretrain/fine-tuning experience, familiar with distributed training