AmazonPosted 1mo ago

Senior GenAI Specialist Solutions Architect, Solutions Architecture

Senior GenAI Specialist Solutions Architect, Solutions Architecture at Amazon scores 70 out of 100 on AI centrality, which makes it a Level 3 role on this board.

TW, TPE, Taipeiseniorfull-time

AI in this role

bedrocksagemaker

ragai-agentsfine-tuningml-ops

Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on AI Specialist Solution Architect (SSA). AWS Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs.
As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. You will craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or designing an entirely new cloud-based system.
SSAs play a critical role in capturing customer feedback, advocating roadmap enhancements, and anticipating customer requirements as they work backwards from their needs. As domain experts, SSAs also participate in field engagement and enablement, producing content such as whitepapers, blogs, and workshops for customers, partners, and the AWS Technical Field.
This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments.

Key job responsibilities
• The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation.
• You’ll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML and Agentic projects.
• Internally, you will be the voice of the customer, sharing their needs with regard to their usage of our services impacting the roadmap of AWS GenAI/ML and Agentic features.
• In this role, your creativity will link technology to tangible solutions, with the opportunity to define cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases.
• You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about running GenAI/ML and Agentic workloads on AWS technology (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
• If you can educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
• Technical Leadership and Mentorship: Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization.

Basic qualifications

- 7+ years of design/implementation/operations/consulting with distributed applications experience
- 5+ years of management of technical, enterprise customer facing resources or equivalent experience
- 5+ years of design/implementation of production AI systems.
- Experience implementing AI solutions that can include integration of LLMs/multi-modal FMs in large scale systems, fine-tuning LLMs, deployment and distributed inference of LLMs, RAG, FM evaluation, Vector DBs, Agentic workflows, prompt/context engineering, and MLOps.
- Hands-on experience with AWS ecosystems (including Bedrock, AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization.

Preferred qualifications

- Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
- Experience in leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion
- Experience communicating to a diverse, global audience
- Experience developing solutions and executing plans on complex projects
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD
- Ability to lead a team or small organization-wide initiative with business objectives that are partially defined
- Ability to influence customer and internal business decision makers as a technical thought leader
- Experience in running and fine-tuning Large and Small Language Models using advanced techniques like LoRA/QLoRA, Instruction Tuning, and RLHF to optimize for specific domain tasks.
- Expertise in architecting AI systems within highly regulated or security-sensitive environments (e.g., Financial Services, Healthcare, Public Sector).

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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagAI AgentsFine TuningMl OpsBedrockSagemaker

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through how you've used Bedrock in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Rag, AI Agents, Fine Tuning, Ml Ops, and Bedrock. 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.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.