Senior Specialist Solutions Architect - Agentic AI, AGS Specialist Solutions Architects

AWS Global Sales (AGS) drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and support for Agentic AI/ML use cases.

Are you a customer-obsessed builder passionate about helping customers achieve their full potential in the AI/ML space? Do you have the business acumen and technical pre-sales expertise to help customers evaluate, design, and adopt AWS as their strategic platform for Agentic AI and ML workloads? Do you like to think big, innovate and simplify Agentic AI & ML solutions? Do you enjoy sharing thought leadership via AWS blogs, open source solutions in GitHub, and drive scaled adoption via 1:many webinars and workshops for customers? Join the AI/ML Specialists Solution Architect team as a Senior Generative AI & ML Specialist Solutions Architect - a senior individual contributor role requiring deep technical expertise, customer engagement at developer and executive level, and deliver impactful technical thought leadership in 1:many webinars and workshops with excellent public speaking skills.

The AGS Specialist organization is part of the customer facing North America (NAMER) sales organization, and is responsible for driving revenue and accelerating adoption of cloud and partner services across diverse customer segments. We work backwards from our customers’ most complex and business-critical challenges to develop and execute go-to-market plans that transform ideas into scalable, high-impact businesses. AGS NAMER teams include sales specialists and technical solution architects. As part of the team, you will contribute across the full lifecycle of AWS customer initiatives—from shaping new service and solution concepts to accelerating adoption of established offerings. We pride ourselves on thinking big, delivering exceptional customer outcomes, and collaborating seamlessly across AWS as #OneTeam.

Key job responsibilities
- Educate and Influence customers at scale (expect 60% of time) with deep technical knowledge, thought leadership, and excellent communication skills via 1:many webinars, hands-on workshops, AWS blogs, solutions in GitHub that help customers accelerate building / enhancing their Agentic AI applications.
- In 1:1 customer engagements, engage with senior engineers, architects, product leaders, data scientists, and executives at strategic enterprise customers to understand their pain points & requirements and influence architectural decisions.
- Design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Bedrock, Amazon AgentCore, Kiro, Amazon Rekognition, Amazon Transcribe, Amazon Quick, Amazon Personalize, and other AI/ML services.
- Be an expert in various ML and AI applied concepts such as model fine tuning, ML Ops, LLMs, RAG, prompt engineering, token & latency optimization, Agent evaluations, AI governance, MCP servers, context engineering & optimization, security & safety for AI agents, loop engineering, etc.
- Build rapid proof-of-concepts for Agentic AI and ML applications based on customer needs and requirements.
- Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for the above mentioned AWS services.
- Thought Leadership – Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
- Act as a technical liaison between customers and the Amazon Bedrock or other AWS service teams to provide customer driven product improvement feedback.
- Advise senior technical and executive stakeholders on architectural trade-offs, risks, and long-term strategy.
- Develop and support an AWS internal community of GenAI related subject matter experts in the AMERICAS.

A day in the life
Your day will be dynamic and impactful. On any given day the activities might include many of the following:
- Lead an architecture and best practices discussion on security, safety, costs, latency, accuracy aspects on AI applications
- Rapidly develop proof of concept (POC) or demo with hours for an upcoming customer conversation to earn their trust
- Contribute to AWS blog
- Test a new AWS service feature before it's released to customers
- Provide a detailed data driven feedback to AWS services team for product feature enhancements
- Create slides & demo for webinar
- Create a hands-on workshop involving multiple AI & ML services, network, storage, database, and analytics services
- Lead, orchestrate, and deliver a 1-many webinar and workshop.
- Engage with business and technical leaders and developers in a 1-2 day experience based accel