Sr Solutions Architect, Annapurna ML

Amazon Amazon · Big Tech · Cupertino, CA · Solutions Architect

This role is for a Sr. Solutions Architect focused on AWS Machine Learning accelerators (Inferentia and Trainium). The individual will work with customers to develop and deploy Deep Learning models on these accelerators, acting as a trusted advisor and thought leader. Responsibilities include designing architectures, owning PoCs, driving adoption through technical engagements, and sharing best practices. The role bridges customer needs with engineering roadmaps and involves creating technical content for various audiences.

What you'd actually do

  1. Design architectures and own Proof of Concept (PoC) solutions for strategic customers, leveraging AWS ML accelerators technologies and the broader set of AWS features and services.
  2. Drive adoption by taking ownership of technical engagements with eco-system partners and strategic customers, assisting with the definition and implementation of technical roadmaps and enabling them to successfully deploy on AWS ML Accelerator.
  3. Develop strong partnership with engineering organizations, serving as the customer advocate, to help drive product roadmap working backwards from customers feedback.
  4. Drive thought leadership by crafting and delivering compelling audience-specific messaging artifacts (product videos, demos, workshops, how to guides etc.) presenting AWS ML accelerator technology through AWS Blogs, reference architectures and solutions, and public-speaking events.
  5. Capture, implement and share best-practices knowledge among the AWS technical community regarding AWS ML Accelerators.

Skills

Required

  • 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
  • 3+ years of design, implementation, or consulting in applications and infrastructures experience
  • 10+ years of IT development or implementation/consulting in the software or Internet industries experience
  • Deep Learning models
  • ML accelerator products
  • AWS ML accelerators technologies
  • AWS ML Accelerator
  • AWS Neuron technology stack

Nice to have

  • 5+ years of infrastructure architecture, database architecture and networking experience
  • Knowledge of SAP systems (like SAP Business Suite, S/4HANA, SAP Business Warehouse, SAP HANA, SAP Business Objects, etc.) and their architecture and infrastructure needs
  • Experience working with end user or developer communities
  • Experience managing relationships with SAP customers and partners
  • Experience in SAP S/4HANA, SAP Cloud Platform, SAP Cloud ERP and Cloud ERP Private
  • Experience in SAP clean core design concepts, including design and build using non-SAP technologies in domains such as Generative / Agentic AI, and data & analytics

What the JD emphasized

  • hands-on experience developing and deploying Deep Learning models
  • integrate it with our ML accelerator products
  • large-scalable production applications
  • developing, deploying and scaling Deep Learning applications on AWS ML accelerators
  • AWS ML accelerator technology
  • AWS Neuron technology stack
  • AWS ML accelerators technologies
  • AWS ML Accelerator
  • AWS ML Accelerator technology
  • AWS ML Accelerators

Other signals

  • customer-facing role
  • work closely with Neuron software development team
  • strategic customers on accelerated Machine Learning solutions
  • hands-on experience developing and deploying Deep Learning models
  • integrate it with our ML accelerator products
  • large-scalable production applications
  • trusted advisor for customers developing, deploying and scaling Deep Learning applications on AWS ML accelerators
  • capturing and sharing best practices and insights
  • shape how AWS ML accelerator technology gets used
  • hands-on partner to AWS services teams, technical field communities, sales, marketing, business development, and professional services, to drive adoption
  • leverage communications skills
  • amplify thought-leadership around AWS Neuron technology stack
  • Design architectures and own Proof of Concept (PoC) solutions for strategic customers
  • leveraging AWS ML accelerators technologies and the broader set of AWS features and services
  • Drive adoption by taking ownership of technical engagements with eco-system partners and strategic customers
  • assisting with the definition and implementation of technical roadmaps
  • enabling them to successfully deploy on AWS ML Accelerator
  • Develop strong partnership with engineering organizations
  • serving as the customer advocate
  • help drive product roadmap working backwards from customers feedback
  • Drive thought leadership by crafting and delivering compelling audience-specific messaging artifacts
  • presenting AWS ML accelerator technology through AWS Blogs, reference architectures and solutions, and public-speaking events
  • Capture, implement and share best-practices knowledge among the AWS technical community regarding AWS ML Accelerators