Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on AI Solution Architect (SA). AWS Solutions Architect - AI are SA's with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SAs work with customers who have complex challenges that require expert-level knowledge to solve. SAs 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. 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, SAs 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 Customers AI ambition into reality
Key job responsibilities • The AI SA 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 Solution Architecture organization.
A day in the life The Solutions Architect-AI team at AWS is responsible for helping customers successfully implement GenAI/AgenticSolutions . In a typical week you will meet multiple customers, and you will collaborate with them on designing and operating well-architected solutions. You will earn their trust and show them the art of the possible, educating them around the capabilities of AWS. Partnering with internal teams and experts, leveraging a deep knowledge of our tools and products, you’ll craft highly scalable, flexible, and resilient cloud architectures that address our customers’ business problems. As part of our team, you’ll have the opportunity to continuously learn and innovate daily.
About the team Cross Industries work hand in hand with AWS customers across mutliple verticals like Auto/Manu, Retail/CPG, HCLS, Travel/Hospitality to help drive AWS GenAI/Agentic services adoption. They are at the crossroads of business and technology and engage with customers of different stages. Supporting the overall technical relationship between customers and AWS, they work to understand the customer's business needs and give prescriptive guidance on how to create business value with technology. Solutions Architects also have broader impact at scale, taking a supporting role in creating and presenting technical content and best practices.
You will be part of a team that is responsible for driving adoption of GenAI/Agentic AWS technologies while bringing differentiated value to customers. This is a team dedicated to some of the largest Brands/Services/Ecommerce customers in India . This customers follow unique technology adoption patterns and growth trajectories that distinguish them from traditional businesses, so you will be employing engagement strategies and programs tailored to their business needs and technical preferences.
Basic Qualifications
- 5+ years of design, implementation, or consulting in applications and infrastructures experience
- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Experience in external enterprise customer-facing role as a technical lead, with strong oral and written communication skills, presenting to both large and small audiences
- 5+ years of management of technical, enterprise customer facing resources or equivalent experience
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- 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.
- 6+ years of design/implementation of production AI systems
Preferred Qualifications
- Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
- Experience developing strategies that influence leadership decisions at the organizational level
- Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering), or Bachelor's degree
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes
- Expertise in architecting AI systems within highly regulated or security-sensitive environments (e.g., Financial Services, Healthcare, Public Sector).
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