AI Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Hands-On Agentic AI Development: You will independently create proof of concepts without depending on a development team for the initial build. This entails designing and coding AI agents utilizing cloud-native services (AWS Bedrock, Azure AI Foundry, Google Vertex AI / Gemini Enterprise Agent Platform) and contemporary agentic frameworks.

• Multi-Cloud Architecture: You will architect scalable infrastructures across the three main hyperscalers and provide recommendations tailored to each client’s specific needs.

• Agentic Framework Design: In addition to individual agents, you will design the cross-platform frameworks that integrate with clients' existing AI stacks, focusing on how agents interact, transfer tasks, and share memory across platforms.

• Client Delivery & Solution Design: You will engage in AI Discovery sessions to pinpoint high-value opportunities within client organizations and collaborate with our AI Strategy and Implementation teams to provide comprehensive solutions.

• Build-vs-Buy and Platform Strategy: You will conduct build-vs-buy assessments for each layer per client, outlining clear advantages and disadvantages based on their current technology stack and team capabilities.

• Governance, Security, and Brand Safety: From day one, you will incorporate policy-as-code, identity management, permissioning, and other security measures into every architecture.

• Team Building & Technical Leadership: You will oversee technical interviews, selection processes, and onboarding for new hires within the AI Labb workstream.

⛳️ Requirements

• Cloud Certification: A minimum of one certification is required, such as AWS Certified Solutions Architect (Associate or Professional), Google Cloud Professional Cloud Architect / Professional Machine Learning Engineer, or Microsoft Azure Solutions Architect Expert.

• Knowledge of Other Clouds: Familiarity with the other two clouds is essential, even if certifications are held for only one.

• Hands-On Coding: Strong expertise in Python is necessary. You should be adept at writing production-quality code, rather than just managing configurations or reviewing pull requests.

• TypeScript or Go: Experience with TypeScript or Go is advantageous due to support for ADK and Strands SDK.

• Cloud Background: A solid foundation in traditional cloud architecture, including networking, IAM, identity, serverless patterns, and infrastructure-as-code, is required.

• AI Stack: Proven experience with at least one hyperscaler AI platform (Amazon Bedrock + AgentCore, Vertex AI Agent Builder + ADK, or Azure AI Foundry) and operational fluency across all three platforms.

• Experience with Vector Databases: Hands-on experience with vector databases such as Pinecone, OpenSearch, pgvector, or similar is expected.

• Agentic Experience: A demonstrated ability to build agents that utilize tools and function calling, with capabilities in memory, planning, and multi-step reasoning is necessary.

• Framework Fluency: Deep, up-to-date knowledge of at least two frameworks including LangGraph, CrewAI, Microsoft AutoGen, Semantic Kernel, Google ADK, AWS Strands, OpenAI Agents SDK, LlamaIndex Agent Workflows.

• LLM Observability: Practical experience with tools such as Openlayer, LangSmith, Arize, Langfuse, or Galileo is required.

• Governance Tooling: Familiarity with policy-as-code and AI governance tools such as OPA, Cedar, NeMo Guardrails, Guardrails AI, Credo AI, or equivalent is desirable.

• Interoperability Standards: Knowledge of MCP (Model Context Protocol) and A2A (Agent2Agent) and their relevance to enterprise agent architectures is important.

• Consulting Mindset: Ability to convey technical concepts to business stakeholders, collaborate with a client's CTO to outline an architecture, and explain its significance to their CEO.

🏝️ Benefits

• Work with Enterprise Clients: Our clientele includes prominent brands in luxury retail, manufacturing, retail, financial services, and healthcare.

• Business-First Philosophy: We navigate through AI hype to deliver tangible value. Every project commences with measurable objectives.

• Direct Leadership Access: You will collaborate closely with our VP of AI Engineering, Principal AI Solutions Architect, Chief AI Strategy Officer, and the CEO.

• Growth Opportunity: As an early member of a growing team, you will have the opportunity to influence our technical trajectory and build the team around you.

• Partnership Ecosystem: Gain access to AWS, Azure, Google Cloud, Snowflake, Databricks, and leading AI/ML platforms.

• Frontier Exposure: Through the Canada AI Alliance and Global AI Leaders Alliance, you'll gain insights into how the most demanding AI organizations are innovating.

• Knowledge Transfer as a Deliverable: Our clients engage us to enhance their internal capabilities, not to foster dependency. You will teach as much as you build.