ANDREW RILEY .

Selected work

Work that connects people, technology and outcomes.

I've spent my career working across the boundaries between business ambition, technical architecture and the people responsible for making change happen.

Andrew Riley presenting to an audience

Selected evidence

Professional outcomes and personal experiments are clearly distinguished. Each is an opportunity to show the problem, approach, decisions and learning.

Personal lab · Applied AI

Designing AI systems with boundaries

Exploring agent identities, scoped permissions, approval gates and observable behaviour as foundations for trustworthy systems.

Personal experiments, not production customer deployments.

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Professional experience · Leadership

Leading teams through technology change

Building architecture capability, developing people and helping enterprise customers navigate complex technology decisions.

Cisco and Google Cloud architecture leadership.

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Personal projects · Engineering

Building to understand

Using homelab infrastructure, automation and AI tooling to make ideas tangible, test assumptions and share practical lessons.

Hands-on projects and writing archive.

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Enterprise experience

Strategy in the boardroom. Capability in the team.

At Cisco, I've led a ten-person architecture team and acted as deputy to the ANZ CTO in strategic engagements. At Google Cloud, I established and led a regional architecture team. The common thread is creating clarity, building trust and enabling people to move forward.

Andrew Riley speaking at a professional event

Applied AI · Personal lab

Beyond the demo: systems that can be understood and governed.

I'm exploring how agents receive identities and permissions, how sensitive actions are approved, and how their behaviour is observed. These are hands-on lab experiments — not claims of production enterprise AI delivery. They help connect new technical possibilities with the enterprise architecture discipline I've developed over my career.

Andrew Riley working on a hands-on project

Engineering through experimentation

Build to learn. Test assumptions. Share the results.

Homelab infrastructure, automation and AI tooling give me a practical environment to explore how systems actually behave. The most useful experiments are the ones that improve the next decision.