Principal GenAI Specialist SA
Listed on 2026-06-26
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Business & Operations
Description
Final date to receive applications:
Jun 29, 2026
Are you passionate about Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), Generative AI, and Agentic AI? Are you energized by the opportunity to drive production usage of ML and AI at scale? We'd love to hear from you.
ML and AI, especially Generative AI and Agentic AI, are rapidly transforming how we work and live. We are witnessing the impact of Generative AI creating everything from code to content, while Agentic AI systems autonomously solve complex business challenges. From home automation and mobile apps to financial trading and shipping logistics, AI is reshaping every industry. Because of the computational scale required for developing AI models, particularly large language models and autonomous agents, the cloud is an ideal environment for deployment, and Amazon Web Services (AWS) leads this space.
We seek someone who is passionate about AI’s potential to help customers understand how it can transform their businesses.
As an AI/ML Specialist Solutions Architect (SA), you will serve as a subject‑matter expert for designing scalable, secure, and cost‑effective AI/ML, Generative AI, and Agentic AI solutions that leverage AWS services. Working at the intersection of innovation and enterprise requirements, you’ll architect production‑grade solutions that are reliable, well‑governed, and compliant with industry standards. Your expertise will be important in helping organizations build responsible AI practices, from traditional ML to advanced Generative AI and Agentic AI systems, while defining robust governance frameworks and secure AI pipelines that scale efficiently.
We’re looking for candidates with deep technical experience across the AI spectrum, from traditional ML and deep learning to Generative AI and Agentic AI, backed by a strong foundation in mathematics and statistics. This includes hands‑on experience with large language models (LLMs) customization/fine‑tuning, inference optimisation, agentic frameworks (e.g., Strands, Lang Graph, CrewaI), GenAIOps/Agent Ops, security, RAG systems optimisation & vector stores, prompt/context engineering, etc.
Candidates should have strong communication skills and technical depth, with the ability to engage stakeholders at all levels, from executives to developers. You’ll need to translate complex technical concepts into clear, actionable insights and work effectively across diverse teams. Previous experience with AWS is valued but not required, provided you have experience building large‑scale solutions. You’ll have the opportunity to work directly with senior engineers at customers, partners, and AWS service teams, influencing roadmaps and driving innovation.
Key Job Responsibilities- Build and maintain technical trusted advisor relationships with influential technical decision‑makers to drive successful adoption and deployment of AWS services, with particular focus on enterprise‑grade AI/ML architectures, Generative AI solutions, and agentic systems.
- Architect scalable, secure, and cost‑effective solutions leveraging AWS’s comprehensive AI stack, from traditional ML services to leading Generative AI offerings, optimizing performance, cost, governance, and responsible AI practices.
- Serve as a thought leader in the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures; create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and GenAIOps best practices, and share insights through AWS blogs, public speaking events, and technical communities.
- Build and nurture an internal AWS community of AI/ML experts, focusing on knowledge‑sharing across traditional ML, Generative AI, and Agentic AI domains, establishing best practices for emerging technologies and creating enablement materials for the broader AWS technical community.
- Collaborate across AWS teams to accelerate customer success with AI/ML implementations, working with business development, professional services, and support teams to ensure effective adoption from proof‑of‑concept to…
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