Sr. Solutions Architect, Annapurna ML

Amazon is hiring a Sr. Solutions Architect, Annapurna ML in Seattle, United States. It pays $177k-$239k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Works on AI ●●●○ is how Level rates this solutions architect role: the daily work is on AI products, without building the model.
The listed pay starts close to the typical solutions architect posting on Level.
Tools and skills the posting cites include Anthropic, PyTorch and TensorFlow.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Drive adoption of Amazon ML accelerators and Neuron SDK by designing architectures and proof-of-concept solutions for strategic customers.

AnthropicPyTorchTensorFlowJAXAWS

deep-learningmachine-learningsolutions-architectureml-accelerators

Annapurna Labs was a startup company acquired by Amazon in 2015, and is now fully integrated. If Amazon is an infrastructure company, then think Annapurna Labs as the infrastructure provider of Amazon. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. Amazon Nitro, ENA, EFA, Graviton and F1 EC2 Instances, Amazon 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.

Amazon Machine Learning accelerators are at the forefront of Amazon 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 Amazon Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. Amazon Neuron and Inferentia are used at scale with customers like Anthropic, Apple, various internal Amazon teams and more customers in various other segments.

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 Amazon ML accelerators. You’ll succeed in this position if you enjoy capturing and sharing best practices and insights, and help shape how Amazon ML accelerator technology gets used. You will be a hands-on partner to Amazon 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 Amazon Neuron technology stack to the broader Amazon field community, as well as our customers.

Key job responsibilities
- Design architectures and own Proof of Concept (PoC) solutions for strategic customers, leveraging Amazon ML accelerators technologies and the broader set of Amazon 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 Amazon 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 Amazon ML accelerator technology through Amazon Blogs, reference architectures and solutions, and public-speaking events.
- Capture, implement and share best-practices knowledge among the Amazon technical community regarding Amazon ML Accelerators.

About the team
The Amazon Annapurna Labs team is a responsible for building innovation in silicon and software for Amazon 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 Amazon cloud infrastructure in networking and security with products such as Amazon Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with Amazon Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with Amazon Neuron SDK, Inferentia and Trainium ML accelerators.

Basic qualifications

- 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
- Experience working with end user or developer communities

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually

How we rate this

Sr. Solutions Architect, Annapurna ML at Amazon rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Sr. Solutions Architect, Annapurna ML is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $177k-$239k a year.
The role is based in US, WA, Seattle.
The job was posted on September 22, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Deep learningMachine learningSolutions ArchitectureML AcceleratorsAnthropicPyTorchTensorFlowJAX

Also common in solutions architect jobs at this level

AWS Python Generative AI Azure LLM Google Cloud

Pay

This job starts at: $177k
Typical solutions architect job: $169k

This posting starts close to the typical solutions architect job. See solutions architect jobs

Questions you could be asked

Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where solutions architecture was part of your work. What did you do?
Tell me about a project where ml accelerators was part of your work. What did you do?
Walk me through how you've used Anthropic in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Deep learning, Machine learning, Solutions Architecture, ML Accelerators, and Anthropic. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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