Sr Solutions Architect, Annapurna ML

You: In this customer-facing role, you will work closely with our Neuron software development team and strategic customers on accelerated Machine Learning solutions. You will bring your hands-on experience developing and deploying Deep Learning models and integrate it with our ML accelerator products, into large-scalable production applications.

You will need to be technically capable and credible in your own right, to become a trusted advisor for customers developing, deploying and scaling Deep Learning applications on AWS ML accelerators. You’ll succeed in this position if you enjoy capturing and sharing best practices and insights, and help shape how AWS ML accelerator technology gets used. You will be a hands-on partner to AWS services teams, technical field communities, sales, marketing, business development, and professional services, to drive adoption. You’ll leverage your communications skills, and be very technical when doing so, to help amplify the thought-leadership around AWS Neuron technology stack to the broader AWS field community, as well as our customers.

Key job responsibilities

• 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 and enabling them to successfully deploy on AWS ML Accelerator.
• Develop strong partnership with engineering organizations, serving as the customer advocate, to help drive product roadmap working backwards from customers feedback.
• 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.
• Capture, implement and share best-practices knowledge among the AWS technical community regarding AWS ML Accelerators.

About the team Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

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

Preferred Qualifications

• 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

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Cupertino - 176,600.00 - 239,000.00 USD annually

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.

The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. AWS Neuron and Inferentia are used at scale with customers like Anthropic, Apple, various internal Amazon teams and more customers in various other segments.

The Team: The Amazon Annapurna Labs team is a responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. Because of our teams breadth of talent, we have been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with AWS Neuron SDK, Inferentia and Trainium ML accelerators.