Secure AI Solution Architect
Amazon
Secure AI Solution Architect
Amazon
Sells products online and rents cloud computing
Amazon Web Services (AWS) is seeking a Secure AI Solution Architect to join our APJC Customer Security team in a content-and-frameworks role. Customers across the region are asking the same questions about building securely with AI — how to give autonomous agents an identity, how to defend against prompt injection, how to govern the AI development lifecycle, how to evidence AI governance for a regulator. The approaches that answer these questions are being proved with customers today; what's missing is the layer that turns them into clean, documented, deployable patterns the whole field can use. You build that layer.
Working hands-on, you take validated approaches and turn them into reference implementations that work out of the box. You test them against real customer requirements, then package them into a published library that Solutions Architects across the region draw on. Your work is the difference between a pattern proved once and a pattern the whole region can reuse.
You are technically self-sufficient: you write the code, build the reference implementation, test it, and document it so a Solutions Architect in any area can adopt it without specialist presence. We are looking for a builder who enjoys taking a defined but difficult technical problem and turning it into an elegant, well-documented answer others can build on. Deep AWS experience helps but is not required at entry; we can teach the services. What we need is strong hands-on technical craft, security depth, and the instinct to build things that scale beyond yourself.
Key job responsibilities
Take validated Secure AI approaches (agentic-AI identity patterns, AI security frameworks, AI development lifecycle controls, guardrail and governance-evidence patterns) and build them into clean, deployable reference implementations — working code, not slideware.
Test each pattern against real customer requirements to confirm it holds, then package it into the published library that the field draws on.
Write the code, reference architectures, and documentation to a standard that a Solutions Architect or partner in any APJC area can adopt without specialist presence.
Work with the AWS service teams (Bedrock, AgentCore, SageMaker) — bringing field requirements and customer data into the product conversation and taking away clarity to turn into guidance.
Stay current on the AWS AI and security product set, translating new and upcoming capability into field-ready reference implementations as it lands.
Surface customer needs and gaps as feature requests, contributing to the feedback loop that shapes what ships next.
A day in the life
You start the morning building out an agentic-identity reference implementation that two areas have asked for. A customer engagement last week surfaced a gap around cross-account tool-use authorisation; you build the fix, test it, and update the library entry so every area gets the improved version.
Mid-morning you join a session with the AgentCore service team. You bring the field data — what APJC customers are hitting on non-human identity — and take away clarity on what can ship as guidance now versus what needs a product change. You'll turn that into an updated reference architecture this week.
After lunch you go heads-down and build — hands on keyboard — turning an AI development lifecycle control you prototyped into a documented reference implementation with code, deployment steps, and a short workshop a field Solutions Architect could run themselves.
You close the day handing the finished pattern to the go-to-market team to fold into the next immersion-day curriculum, publishing the write-up to the field, and briefing the Associate SA on what's ready to be packaged into next week's community event. No two days look the same, but the thread is consistent: you build it once, and the whole region gets to build on it.
About the team
APJC Customer Security helps customers across the region adopt AI on AWS with confidence — ensuring security, risk, and regulation accelerate AI adoption rather than slow it down. We run two coupled programmes: Secure AI (making AWS the best place to build securely with AI) and AI for Security (using AI to help customers defend themselves). As one of two Solution Architects, you build the reusable technical foundation both programmes scale on. You work with the AWS service teams who build the products and the field teams who take guidance to customers. You will have a clear development path, a peer community of specialists, and see your work reused across the entire region.
- 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 2+ years of design, implementation, or consulting in applications and infrastructures experience
- 10+ years of IT development or implementation/consulting in the software or Internet industries experience
- Experience working within software development or Internet-related industries
- Experience migrating or transforming legacy customer solutions to the cloud
- Experience working with AWS technologies from a dev/ops perspective
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Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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