About the role
AI summarisedAWS is seeking an AI Specialist Solution Architect to lead the adoption of GenAI/ML and Agentic technologies. The role involves designing scalable cloud architectures, building technical relationships with customers, and creating best practices and content. The ideal candidate has deep expertise in AI/ML and experience with production AI systems.
BusinessFull-timeSolutions Architect
Key Responsibilities
- Build 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.
- 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, 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.
- Link technology to tangible solutions, with the opportunity to define cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases.
- 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).
- Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization.
Requirements
- 5+ years of management of technical, enterprise customer facing resources or equivalent experience.
- Experience communicating complex concepts clearly and persuasively to different audiences.
- 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.
- Ability to influence customer and internal business decision makers as a technical thought leader.
- Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes.
- Ability to lead a team or small organization-wide initiative with business objectives that are partially defined.
- Strong ability to determine solution strategy and where to simplify or extend solutions for the best outcome.
- 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).