Senior AI Specialist Solutions Architect, AWS
Amazon is hiring a Senior AI Specialist Solutions Architect, AWS in Singapore, Singapore. Level rates it ; you can apply on Level.
AI in this role
Design scalable cloud-native GenAI and machine learning architectures as a senior AI specialist solutions architect at AWS.
SSAs work with customers who have complex challenges that require expert-level knowledge to solve. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or design an entirely new cloud-based system.
Specialist SAs play a critical role in capturing customer feedback, advocating for 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).
• Technical Leadership & Mentorship: Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization.
A day in the life
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
About the team
This position is part of the Amazon Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to help our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges.
About the team
This position is part of the Amazon Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to help our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges.
Basic qualifications
- 7+ years of design, implementation, or consulting in applications and infrastructures experience
- 5+ years of management of technical, enterprise customer facing resources or equivalent experience
- 5+ years of design/implementation of production AI systems
Preferred qualifications
- 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.
- Able to effectively communicate across an increasing diversity of audiences internally and externally
- Ability to influence customer and internal business decision makers as a technical thought leader
- Cloud Technology Certification
- Experience leading and influencing your team or organization, or experience writing low level drivers
- Experience selling nascent products and services Ability to drive solutions to difficult problems
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD
- Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes
- Experience in running & 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.
How we rate this
Senior AI Specialist Solutions Architect, AWS at Amazon rates 70 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.
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. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical solutions architect job
- $168k
This posting doesn't list pay. Use the typical solutions architect figure when pay comes up. See solutions architect jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a project where solutions architecture was part of your work. What did you do?
- Tell me about a project where genai 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?
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, Solutions Architecture, Genai, and Machine learning. 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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