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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Specialist Solutions Architect, Enterprise, AGS US Specialist SA - **Company:** Amazon.com, Inc. - **Location:** Irvine, CA, United States - **Experience:** Experienced - **Salary:** $151,000.0 - $204,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Systems Engineering, Cloud Computing, Machine Learning, Azure Machine Learning, SAS (Software), Software Engineering, Chatbots, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Kubernetes, Data Analytics, Machine Learning Operations, Virtual Agents - **Published:** August 16, 2026 - **Apply:** https://dejobs.org/x/x/6FB81D26B86C42E1B8794B5E8C44B8C2/job/ ## About the Role You must have deep technical experience working with technologies related to generative AI, machine learning, and/or deep learning. Hands-on experience building applications on foundation models (RAG pipelines, agent frameworks, prompt engineering, model evaluation, fine-tuning) is required. A strong mathematics and statistics background is preferred in addition to experience with solution architecture and production ML systems. You should be familiar with the GenAI ecosystem (model providers, orchestration frameworks, vector databases, evaluation tools) and will leverage this knowledge to help AWS customers evaluate tradeoffs and accelerate their AI adoption., * 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience * 2+ years of design, implementation, or consulting in applications and infrastructures experience, * Experience working within software development or Internet-related industries * Experience migrating or transforming legacy customer solutions to the cloud * Experience working with AWS technologies from a dev/ops perspective ## Description Working with customers' development, data science, and AI engineering teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of the AWS cloud platform and AWS AI/ML services including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, Amazon Nova foundation models, Amazon Quick, Kiro, Amazon Comprehend, Amazon Rekognition, Amazon Textract, and Amazon Transcribe. Partner with SAs, Sales, Business Development, and the AI/ML service teams to accelerate customer adoption and revenue attainment in the AMERICAS for AWS generative AI and machine learning services, with a focus on Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, and the agentic AI portfolio. Thought Leadership: Evangelize AWS GenAI/ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures, sample code repositories, and public-speaking events such as AWS Summit, AWS re:Invent, etc. Act as a technical liaison between customers and the AWS Bedrock, AgentCore, SageMaker, and broader AI/ML service teams to provide customer-driven product improvement feedback and feature requests. Develop and support an AWS internal community of GenAI-related subject matter experts in the AMERICAS, enabling field teams to identify, qualify, and position generative AI and agentic AI opportunities with their customers. A day in the life Most of your time is spent working directly with customers, helping them figure out how to use generative AI and machine learning to solve real business problems. On a given morning, you might be on a video call with a team of engineers at a large company who want to build an AI agent that can process invoice documents. You're sketching out an architecture on a virtual whiteboard, asking questions about their data, and helping them think through tradeoffs between different approaches. That afternoon, you're prepping a demo for a different customer who's evaluating AWS against a competitor for a conversational AI use case. Later in the week, you're on-site running a workshop where a customer's ML team is building their first retrieval-augmented generation pipeline with you guiding them through it hands-on. You're typically focused on a single industry (think financial services, or healthcare, or manufacturing), so you build real familiarity with the problems, regulations, and data challenges in that space. You'll work with many different companies within your industry rather than being embedded at one or two for years. Some engagements last a few weeks, others stretch over a couple months, but the variety keeps things interesting. Between customer conversations, you're building things that help others learn what you know: writing a blog post about a pattern you've seen work well, recording a short demo, or building a reference architecture that your peers across the country can reuse. You're also spending time helping other technical teams across the org understand how to spot AI/ML opportunities in their customer conversations. Beyond the regular rhythm, some weeks bring unexpected moments that make this role special. You might get asked to present a customer success story to an audience of thousands at re:Invent, or get early access to a new service months before launch and help shape how it works based on what you've seen customers struggle with. Occasionally you'll find yourself in an executive briefing room explaining agentic AI to a Fortune 500 CTO who's deciding where to place a multi-million dollar bet. Travel runs about 20-30%, mostly for customer workshops, executive briefings, and AWS events. ## Related Videos - [The State of GenAI & Machine Learning in 2025](https://www.wearedevelopers.com/videos/1383-the-state-of-genai-machine-learning-in-2025) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) - [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)