Sr AI Solution Architect, AI Specialist Solutions Architect team

Amazon; City of Melbourne; On-site; AUD 150,000 - 200,000; Full time

Job summary

Amazon is seeking a Sr AI Solution Architect in Melbourne, Victoria, to lead the adoption of AI solutions and provide hands-on expertise to customers. The ideal candidate will possess deep knowledge in AI architecture and a strong background in cloud computing.

Your role will involve managing technical relationships, guiding customers through their cloud journey, and creating best practices for utilizing AWS's advanced AI solutions. A Master's degree or PhD in a relevant field is highly preferred.

Qualifications

• 7+ years of design, implementation, or consulting in applications and infrastructures experience.
• 5+ years of experience in software development or cloud computing.
• Hands-on experience with AWS services for AI environments.

Responsibilities

• Build technical relationships with customers to enhance their AI implementations.
• Manage technical relationships providing recommendations to improve performance.
• Create and share best practices and technical content for AWS technologies.

Skills

AI architecture

Cloud computing

Customer engagement

Technical leadership

Project management

Education

Master's degree or PhD in computer science or related field

Tools

AWS ecosystems (Bedrock, AgentCore, SageMaker)

Vector databases

Retrieval-Augmented Generation techniques

Job description

Sr AI Solution Architect, AI Specialist Solutions Architect team

Job ID: 10445643 | Amazon Web Services Australia Pty Ltd

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 operates 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.

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 & 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).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.