Sr. AI Partner Solution Architect, ANZ Partner Team
Amazon Web Services
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Questions you are likely to be asked
- Why do you want to join Amazon Web Services?
- What is your experience with AWS? Tell me one thing you learned the hard way.
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
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Practise the Sr. AI Partner Solution Architect, ANZ Partner Team at Amazon Web Services interview free →Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a Senior AI Partner Solutions Architect (PSA) to join our ANZ Partner Solutions Architecture team. In this role, you will Basic qualifications: - 10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience - 5+ years of design and implementation of production AI/ML systems, including recent experience with Generative AI, large language models, or agentic AI solutions - Experience implementing AI solutions that may include integration of LLMs/multi-modal foundation models, RAG, vector databases, agentic workflows, prompt engineering, and MLOps - Experience communicating with and presenting to technical and non-technical executive audiences, including C-level stakeholders Preferred: - Experience with agentic AI solution frameworks (e.g., LangGraph, CrewAI, ADK) and complex agentic patterns (e.g., ReAct, self-reflection, hierarchical delegation) - Hands-on experience with AWS AI ecosystem including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon Quick, Kiro, Amazon SageMaker, and AWS Strands Agents SDK. - Working familiarity with AI developer tooling from AWS partners such as Anthropic Claude Code, OpenAI Codex, or similar AI-powered development platforms. - Hands-on-experience on multi-agent orchestration patterns, Model Context Protocol (MCP), Agent-to-Agent (A2A) protocols, and memory management strategies. - Experience in running and fine-tuning large and small language models using techniques such as LoRA/QLoRA, instruction tuning, and RLHF. - Working knowledge of "Large Language Models (LLMs)-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. Acknowledgement of country: In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today. IDE statement: Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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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Listed on amazon · posted 2026-06-02. ApplySarthi collects openings and links to application pages; the role is advertised by Amazon Web Services, not by us.