Snr. Solutions Architect in Sydney

Are you interested in supporting Australia and New Zealand (ANZ) startups challenging the development of generative AI foundation models and large language models? Would you like to leverage your entrepreneurial experience, development capabilities, technical expertise, business knowledge, and communication skills? Amazon Web Services is seeking a Solutions Architect based in Singapore to support ANZ startups tackling model development through architecture reviews and technical mentoring.

We are looking for candidates who can lead discussions on effective training and inference environments using AWS, along with associated cloud architectures, through face-to-face and written communication with customers, drawing from deep technical insights in model training and inference. This role may have ~30% travel across ANZ countries to engage directly with customers onsite and provide hands-on technical support. We also welcome those interested in improving and enhancing AWS services to make them more accessible for startup customers.

Additional responsibilities include supporting Go-to-Market initiatives for customer-developed models, strategic planning with regional and international Generative AI team members, speaking at events, writing blog posts, and participating in community activities. The ideal candidate will enjoy supporting the growth of startup companies challenging the development of generative AI foundation models and large language models from both technical and business perspectives across the ANZ.

Key job responsibilities:

• Understand customer challenges in generative AI foundation model development, training, fine-tuning, and inference across customers in ANZ, and propose optimal computing resources, storage solutions, and AWS architectures.
• Influence and build trust with CTOs and technical decision-makers at generative AI startups throughout the ANZ area.
• Stay current with AWS services and mechanisms needed for generative AI model development through customer conversations, and drive improvements.
• Collaborate with internal stakeholders including sales, business development, and global service development teams on strategic planning for the ANZ area.
• Author and develop technical content such as blog posts, sample code, and demos to help generative AI startups solve technical challenges and accelerate time to service launch.
• Deliver technical presentations and discussions on generative AI with customers at AWS events across ANZ.
• Provide feedback on startup requirements to AWS service teams and contribute to service improvements.

The AWS Startup Solutions Architecture team is dedicated to working with startup companies as they build their businesses. We're here to help them deploy the best, most scalable, most secure, cost-effective and easy to operate architectures. Startups are the large enterprises of the future. These young companies are founded by ambitious people who have a desire to build something meaningful and to challenge the status quo.

About the team: The AWS Startup Solutions Architect team provides technical support to startup companies across a wide range of stages, from pre-launch to exit. You will grow personally while being inspired by entrepreneurial team members who are passionate about supporting the growth of ANZ startups. You will work in collaboration with other teams such as sales, business development, and marketing.

Basic Qualifications:

• 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
• 8+ years of design, implementation, or consulting in applications and infrastructures experience.
• 8+ years of IT development or implementation/consulting in the software or Internet industries experience.
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients.
• Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware.

Preferred Qualifications:

• Experience working with end user or developer communities.
• 2+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience.
• Experience influencing C-level executives/start-ups.
• Experience leading teams and driving results through team members.
• Master's degree or equivalent in computer science, machine learning, engineering, or related fields, or experience working with or evaluating AI systems.