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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Solutions Architect, Annapurna ML - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $176,600.0 - $239,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Systems Engineering, Cloud Computing, Databases, Network Interface Controllers, Field-Programmable Gate Array (FPGA), Hardware Design, Machine Learning, Software Engineering, IT Architecture, Deep Learning, Information Technology, Data Analytics, Nvme - **Published:** September 23, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28044362/Sr-Solutions-Architect-Annapurna-Ml-Washington-Seattle-7375 ## About the Role 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 ## Description 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)