AI Engineer building LLM - powered and agentic features for Toronto’s home - management platform. Shipping intelligent maintenance, matching, document, and conversational experiences through Python and TypeScript.
About the role
- AI Architect developing and deploying AI solutions across various industries. Coding and architecting AI systems with AWS and Agentic AI for enterprise clients.
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 AWS Bedrock and frameworks like LangChain or LangGraph, implementing reasoning, planning, and memory modules.
- AWS Cloud Architecture (PaaS Focus): 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.
- Client Delivery & Solution Design: 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.
- Team Building & Technical Leadership: 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.
- Multi-Cloud & Integration: 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.
Requirements
- AWS Certification: Must hold a valid AWS Certified Solutions Architect (Associate or Professional).
- Hands-On Coding: Strong proficiency in Python. You must be comfortable writing production-grade code, not just managing configurations or reviewing pull requests.
- Cloud Background: Strong foundation in traditional Cloud Architecture including networking, IAM, and serverless patterns. We expect you to have built cloud infrastructure before moving into AI.
- AI Stack: Proven experience with Amazon Bedrock, SageMaker, and Vector Databases such as Pinecone or OpenSearch.
- Agentic Experience: Demonstrated ability to build Agents that utilize tools and function calling. We are not looking for people who have only built simple chatbots.
- Consulting Mindset: Ability to communicate technical concepts to business stakeholders and translate business problems into technical solutions.
Benefits
- Work with Enterprise Clients: Our client roster includes major brands across manufacturing, retail, financial services, and healthcare.
- Business-First Philosophy: We cut through AI hype to deliver real value. Every project starts with measurable objectives.
- Direct Leadership Access: You will work closely with our VP of AI Engineering, Principal AI Solutions Architect, and Chief AI Strategy Officer.
- Growth Opportunity: As an early member of a scaling team, you will shape our technical direction and build the team around you.
- Partnership Ecosystem: Access to AWS, Azure, Google Cloud, Snowflake, Databricks, and leading AI/ML platforms.
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