Agentic AI Architect
About AI Labb
AI Labb is the Data & AI division of TheAppLabb , a technology innovation firm that has launched 750+ applications over the past 18 years for global brands including Suncor, Loblaw, Petro Canada, RBC, Porter Airlines, Chatters, David Yurman, Meridian, Empire Life, First Canadian Title, Gateway Casinos, and the Canadian Standards Association.
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.
Our work increasingly takes us beyond individual AI use cases into designing enterprise agentic frameworks — the orchestration, observation, and decision-modelling layers that unify our clients' existing AI platforms into coherent, governable, brand-safe systems. We are connected into the Canada AI Alliance and Global AI Leaders Alliance networks, giving us cross-industry visibility into how the most demanding AI organizations are building.
Role Summary
We are looking for a hands-on AI Architect who can code, architect, and deploy across AWS, GCP, and Azure. You must be able to take a concept from a whiteboard to a working Proof of Concept independently, and you must also be able to step up a level — designing the cross-platform agentic frameworks our enterprise clients need to scale AI safely.
This role combines deep multi-cloud architecture expertise with modern agentic AI patterns to build autonomous systems that solve real business problems. You will work directly with clients across retail, luxury, financial services, healthcare, and manufacturing, translating 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.
The role is hands-on at the PoC stage and architectural at the framework stage — you should be equally comfortable shipping production-grade Python and producing a reference architecture a client's CTO will build against for the next two years.
Core Responsibilities
Hands-On Agentic AI Development
You will build PoCs independently without relying on a dev team for the initial build. This means designing and coding AI agents using cloud-native services (AWS Bedrock, Azure AI Foundry, Google Vertex AI / Gemini Enterprise Agent Platform) and modern agentic frameworks (LangChain, LangGraph, CrewAI, Microsoft AutoGen, Semantic Kernel, Google ADK, AWS Strands, OpenAI Agents SDK). You will implement reasoning, planning, and memory modules; configure LLMs to interact with external APIs, databases, and enterprise software to execute real-world tasks. Our clients expect working demonstrations, not slide decks.
Multi-Cloud Architecture
You will design scalable infrastructure across all three major hyperscalers and recommend the right one for each client's situation:
- AWS: Bedrock, Bedrock AgentCore, Strands Agents, AgentCore Policy, Lambda, Fargate, API Gateway, EventBridge, Step Functions, SageMaker.
- GCP: Gemini Enterprise Agent Platform / Vertex AI Agent Builder, Agent Development Kit (ADK), Agent Engine, Agent Studio, BigQuery, Cloud Run, Vertex AI Pipelines.
- Azure: AI Foundry, Copilot Studio, Semantic Kernel, Azure OpenAI Service, Azure Functions, Container Apps, Logic Apps.
You will select and optimize foundation models across providers (Bedrock, Vertex Model Garden, Azure OpenAI) based on cost, latency, performance, and data residency requirements. All architectures must meet strict security, compliance, and cost-optimization standards.
Agentic Framework Design (Orchestration, Observation, Decision Modelling)
Beyond individual agents, you will architect the cross-platform frameworks that sit above clients' existing AI stacks:
- Orchestration: Design how agents communicate, hand