Senior GenAI Solutions Architect

Amazon; Auckland; On-site; NZD 150,000 - 210,000; Full time

Job summary

Amazon Web Services New Zealand Limited seeks a Sr AI Solution Architect in Auckland to design and implement GenAI/ML and Agentic workloads on AWS. You translate business needs into scalable cloud architectures and guide secure, cost-effective deployments for customers.

This role blends deep technical leadership with hands-on delivery, collaborating with customers, partners, and internal teams to create reference architectures, workshops, and best practices for production AI systems.

Qualifications

• As part of the AWS sales organization, SSAs translate customer needs into scalable GenAI/ML architectures.
• Hands-on experience with AWS ecosystems and practical knowledge of RAG, embeddings, and LLMs is required.
• Experience leading technical, customer-facing resources and delivering reference architectures.

Responsibilities

• Build trusted technical relationships with customers and guide GenAI/ML adoption on AWS.
• Recommend secure, cost-optimized, high-performance architectures for complex projects.
• Communicate customer needs to product teams and contribute to roadmaps.
• Define cloud-native GenAI/ML and Agentic architectural patterns for multiple use cases.
• Create and share best practices, whitepapers, and reference architectures; lead workshops and talks.
• Lead hands-on deep dives and tutorials; develop reusable assets for the engineering org.

Skills

Cloud computing

Software development

Systems engineering

Infrastructure

Security

Networking

Data & analytics

MLOps

Technical leadership

GenAI/ML architectures

Education

Master's degree or PhD in CS/Math/ML

Tools

Bedrock

AgentCore

SageMaker

Vector stores

Job description

Amazon Web Services New Zealand Limited seeks a Sr AI Solution Architect in Auckland to design and implement GenAI/ML and Agentic workloads on AWS. You translate business needs into scalable cloud architectures and guide secure, cost-effective deployments for customers.

This role blends deep technical leadership with hands-on delivery, collaborating with customers, partners, and internal teams to create reference architectures, workshops, and best practices for production AI systems.