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A technology innovation firm in Toronto is seeking a hands-on AI Architect to code, architect, and deploy AI solutions. This role involves working with clients across various industries, leading technical initiatives, and implementing scalable infrastructure using AWS. The ideal candidate will have strong background in cloud architecture and proven experience with AI tools. The firm values a business-first philosophy and provides opportunities to shape the technical direction of the growing team.
AI Labb is the Data & AI division of TheAppLabb, a technology innovation firm with 18+ years of experience and 750+ applications launched for industry leaders including Suncor, RBC, Petco, and CSA Group. We bridge the gap between AI's promise and business reality, delivering pragmatic AI solutions that create measurable business outcomes rather than theoretical possibilities.
Our approach is business‑first: we start with client objectives and work backward to ensure every AI initiative delivers measurable ROI. We are looking for builders who share this philosophy.
We are looking for a hands‑on AI Architect who can code, architect, and deploy. You must be able to take a concept from a whiteboard to a working Proof of Concept independently. This role combines deep AWS Cloud Architecture expertise with modern Agentic AI patterns to build autonomous systems that solve real business problems.
You will work directly with clients across manufacturing, retail, financial services, and healthcare, translating their business challenges into working AI solutions. You will also play a key role in growing the AI Labb team by technically vetting and onboarding future engineers.
You will build PoCs independently without relying on a dev team for the initial build. This means designing and coding AI Agents using AWS Bedrock and frameworks like LangChain or LangGraph, implementing reasoning, planning, and memory modules. You will configure LLMs to interact with external APIs, databases, and enterprise software to execute real‑world tasks. Our clients expect working demonstrations, not slide decks.
You will design scalable infrastructure using AWS PaaS services including Lambda, Fargate, API Gateway, EventBridge, and Step Functions. You will select and optimize Foundation Models via Amazon Bedrock or SageMaker based on cost, latency, and performance requirements. All architectures must meet strict security, compliance, and cost‑optimization standards.
You will participate in AI Discovery engagements to identify high‑value opportunities within client organizations. You will translate business requirements into technical architectures that align with our outcome‑driven methodology. You will work alongside our AI Strategy and Implementation teams to deliver end‑to‑end solutions.
You will lead technical interviewing, selection, and onboarding for new hires within the AI Labb workstream. You will define technical standards and coding guidelines for our growing AI/ML team. You will contribute to knowledge transfer initiatives, building client capabilities rather than dependencies.
You will integrate AI services into existing enterprise workflows and data pipelines. You will maintain operational knowledge of Azure and GCP to support client‑specific multi‑cloud requirements.
AI Labb delivers solutions across several domains. Here are examples of the types of projects you would contribute to:
Building multi‑agent systems that reduce manual decision‑making by 30% and improve response times by 40%. Implementing AI‑driven quality monitoring for manufacturing clients that reduces batch rejections by 25%. Developing hyper‑personalization engines for retail clients that increase digital conversion rates by 20‑27%. Creating data pipelines and AI infrastructure that enable new AI initiatives while reducing data preparation time by 60%.
Send your resume along with one of the following: a link to a GitHub repo showing an agentic AI project you have built, a brief write‑up describing a complex AI system you have architected, or a demo video of a PoC you have created.
We want to see evidence that you can build, not just design.