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Solutions Architect III, AGS MENAT Specialist Team
Are you passionate about Machine Learning, Deep Learning, and Artificial Intelligence? Join AWS as a Generative AI and Machine Learning Specialist Solutions Architect in the MENAT region, where you'll drive cutting-edge AI initiatives and business transformation. As a Subject Matter Expert for designing machine learning solutions, you'll leverage AWS services to automate solutions and reduce costs for customers.
You'll partner closely with GenAI/ML specialist sales teams along with field teams to enable large-scale customer use cases and drive adoption of AWS GenAI/ML solutions. Your expertise will shape machine learning architectures, develop technical assets, and create field enablement materials that help other Solutions Architects integrate AWS GenAI/ML solutions into customer environments. This role offers an exciting opportunity to be at the forefront of GenAI innovation in a region implementing numerous transformative AI initiatives.
- Key job responsibilities
- Design and architect scalable, secure, and innovative GenAI solutions that leverage AWS services to solve complex customer challenges and drive business transformation.
- Build and maintain technical trusted advisor relationships with influential technical decision makers for successful adoption and deployment of AWS GenAI/ML services and technologies.
- Evangelize current and future AWS GenAI and ML services through white papers, blogs, reference implementations, and presentations to enable customers and partners.
- Capture and share best-practice knowledge amongst the AWS solutions architect community, creating field enablement materials for the broader SA population.
- Work collaboratively with sales teams to create and execute business plans that accelerate AWS adoption, exceed revenue goals, and drive customer satisfaction with GenAI/ML solutions.
A day in the life
Your day begins with a technical deep dive with a customer's AI team to understand their GenAI requirements and propose architecture solutions using Amazon Bedrock and Sage Maker. Later, you'll collaborate with sales colleagues on business plans for driving AI adoption, then spend time developing a reference architecture for a RAG solution that addresses common customer needs. You might finish by drafting a technical blog on implementing ML solutions or conducting a workshop to demonstrate AI capabilities to potential customers.
About the team
You'll join AWS's innovative team in the MENAT region where numerous AI initiatives are being driven. As part of the AGS MENAT Specialist organization, you'll work alongside talented technical professionals who are transforming how businesses leverage AI technologies. The team fosters an inclusive culture that values continuous learning and professional growth, providing opportunities to collaborate on groundbreaking projects that shape the future of AI adoption across diverse industries in the region.
Basic Qualifications
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- Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 5+ years of professional or military experience
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- 10+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
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- Experience building services using AWS products
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- Experience with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and agentic workflows.
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- Proficiency in Python and experience with GenAI frameworks (Lang Chain, Llama Index, etc.) and model APIs.
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- Experience participating in the sales lifecycle (directly or indirectly) for GenAI solutions.
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- Experience in leading executive briefings and customer workshops focused on GenAI strategy, use case development, and prototype demonstrations.
Preferred Qualifications
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- Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or PhD
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- Experience prioritizing competing demands, scoping large efforts, and negotiating timelines
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- Experience with enterprise-scale infrastructure or development-based cloud programs/projects in a related industry
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- Experience conveying complex technical concepts to both technical and business audiences
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- Publications or presentations in recognized GenAI, NLP, or ML journals or conferences.
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- Hands-on experience architecting and deploying production GenAI solutions in secure or regulated environments.
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- Deep technical expertise with AWS GenAI services including Amazon Bedrock (Claude, Llama, Titan models), Amazon Sage Maker Jump Start, Amazon Q, and related AWS services (Lambda, Step Functions, ECS/EKS, API Gateway).
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- Experience with GenAI security patterns, responsible AI practices, and model governance.
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- Ability to collaborate with global/enterprise account sales and delivery teams to drive adoption of GenAI Solutions into top accounts.
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- Ability to think strategically about business, product, and technical problems in the GenAI space and develop strategic, data-driven approaches.
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.
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
10条评价
3.4
10条评价
工作生活平衡
2.5
薪酬
4.2
企业文化
3.0
职业发展
3.8
管理层
2.7
65%
推荐率
优点
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
缺点
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
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4个数据点
L2
L6
L3
L4
L5
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试评价
6条评价
难度
4.0
/ 5
时长
21-35周
体验
正面 0%
中性 17%
负面 83%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
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Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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