Sr AI Solution Architect, AI Specialist Solutions Architect team

Amazon Web Services; City of Melbourne; On-site; AUD 180,000 - 260,000; Full time

Job summary

Amazon Web Services leads the AI transformation by enabling customers with expert AI Specialist Solutions Architects. You will design scalable GenAI/ML architectures, mentor teams, and help customers deploy secure AI workloads on AWS.

The role emphasizes hands-on architecture work, content creation, and active engagement with customers to drive adoption of GenAI/Agentic technologies across industries.

Qualifications

• 7+ 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.
• Ability to influence customer and internal business decision makers as a technical thought leader and communicate across diverse audiences.
• Hands-on experience with AWS ecosystems to set up secure, private-network AI environments and practical RAG implementations.
• Experience implementing AI solutions including LLMs, model fine-tuning, deployment, distributed inference, and MLOps.
• 6+ years of design/implementation of production AI systems.
• 5+ years management of technical, customer facing resources.

Responsibilities

• Build trusted technical relationships with customers and act as a trusted advisor across GenAI/ML initiatives.
• Recommend secure, cost-effective, high-performing architectures for GenAI/ML projects.
• Voice of the customer, informing roadmap and feature needs for GenAI/ML capabilities.
• Define cloud-native GenAI/ML and Agentic architectures for varied use cases.
• Create and share best practices, reference architectures, and educational content (white papers, blogs, workshops).
• Lead hands-on deep dives and technical workshops; contribute reusable assets for the engineering org.

Skills

7+ years experience

Domain experience (software/cloud)

Technical leadership

AWS ecosystems (Bedrock, AgentCore, S6

Education

Master's degree in CS/ML or related

PhD in a quantitative field

Tools

Bedrock

AgentCore

SageMaker

RAG & Vector DBs

Job description

Sr AI Solution Architect, AI Specialist Solutions Architect team

Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands‑on AI Specialist Solution Architect (SSA). AWS Specialist Solutions Architects (SSAs) are technologists with deep domain‑specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert‑level knowledge to solve. SSAs 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. Specialist 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, SSAs 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 AI ambition into programs that can be delivered, operated, and scaled in production environments.

Key job responsibilities

• The AI Specialist SA team 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 engineering organization.

About the team

#genai

Basic qualifications

• 7+ 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
• Ability to influence customer and internal business decision makers as a technical thought leader and ability to effectively communicate across an increasing diversity of audiences internally and externally
• 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.
• 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.
• 6+ years of design/implementation of production AI systems
• 5+ years management of technical, customer facing resources

Preferred Qualifications

• Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
• 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
• Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes
• Technical Cloud Certification & a Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD
• 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).

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

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