Description
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 SageMaker. 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
- - 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
- - 10+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- - Experience building services using AWS products
- - Experience with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and agentic workflows.
- - Proficiency in Python and experience with GenAI frameworks (LangChain, LlamaIndex, etc.) and model APIs.
- - Experience participating in the sales lifecycle (directly or indirectly) for GenAI solutions.
- - Experience in leading executive briefings and customer workshops focused on GenAI strategy, use case development, and prototype demonstrations.
Preferred Qualifications
- - 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
- - Experience prioritizing competing demands, scoping large efforts, and negotiating timelines
- - Experience with enterprise-scale infrastructure or development-based cloud programs/projects in a related industry
- - Experience conveying complex technical concepts to both technical and business audiences
- - Publications or presentations in recognized GenAI, NLP, or ML journals or conferences.
- - Hands-on experience architecting and deploying production GenAI solutions in secure or regulated environments.
