AI Implementation Engineer (Azure AI, Agents & Automation)

AI Implementation Engineer (Azure AI, Agents & Automation) Location: Vancouver, BC (Hybrid) Type: Full-time, Permanent Reports to: VP of Engineering About Tribe Tribe Property Technologies is modernizing one of Canada’s most traditional industries — property management — through technology and community-driven innovation.

Our platform, Tribe Home, connects residents, managers, and service providers in one ecosystem.

We’re now taking the next leap: embedding AI and automation across Tribe as a whole (internal operations and customer-facing experiences) while keeping security, reliability, and Canadian data residency front and center.

The Role We’re looking for a hands-on AI Implementation Engineer to help us design, improve, and deploy production-grade AI systems and automations across Tribe. This role spans both internal automation and customer-facing AI: Internal: high-impact workflow automation that reduces friction for staff Customer-facing: AI capabilities embedded into Tribe Home that improve the community management experience and resident service Work in a modern Azure-based environment (Azure SQL, .NET, React, SQL Server, MongoDB).

Build solutions using: Azure AI Foundry / Azure OpenAI Copilot Studio + Power Automate Microsoft Fabric (Lakehouse and data readiness) Leverage MCP (Model Context Protocol) to integrate and orchestrate AI capabilities across systems.

What Success Looks Like In the first 90 days Review our existing AI implementations in Azure and identify architecture + reliability improvements Implement key improvements (patterns, guardrails, observability, integration approach) Deliver a clear strategy to support the next 12–24 months of goals Ship one high-value internal automation that meaningfully reduces time and friction for staff In 12 months (home run) Be a key designer and implementer of Tribe’s AI systems (internal + Tribe Home) Establish reusable implementation patterns (including MCP tool patterns) the team can follow Deliver multiple meaningful automations and AI features with measurable outcomes Raise the bar on AI reliability (testing, evaluation, monitoring) across what we build What You’ll Do Evaluate and improve existing AI architecture and implementations in Azure (reliability, scalability, security, cost) Build RAG (retrieval-augmented generation) and agentic workflows that safely take actions with appropriate guardrails Design and implement AI orchestration using Azure AI Foundry / Azure OpenAI, and integrate with Power Automate / Copilot Studio where it makes sense Extend and operationalize our MCP server as a tools abstraction layer: design MCP tools over APIs/legacy systems enforce permissions, auditability, and safe action patterns Work with Product and Engineering to deliver customer-facing AI in Tribe Home (e.g., ticket triage/summarization, knowledge retrieval over documents) Identify and implement high-value internal automations (approvals, routing, document-triggered workflows, reporting) Contribute to data readiness work (Fabric/Lakehouse exposure, data quality expectations, AI-ready datasets) Implement AI reliability practices: prompt/context patterns, evaluation, human-in-the-loop design, monitoring/telemetry Collaborate with IT, Operations, and Service Delivery as secondary partners to ensure solutions work in real workflows Mentoring is valuable but secondary; we primarily need a strong builder who can also guide patterns by example.

What You Bring Required 4+ years in software engineering, automation engineering, or similar (strong “builder” track record) Experience with .NET and C# in production environments Proven experience implementing AI systems using Azure OpenAI / Azure AI services (or equivalent production LLM systems) Strong integration skills: APIs, authentication, data access patterns, event-driven workflows Experience building RAG systems and/or agentic workflows with clear reliability and safety patterns Comfort writing code to solve orchestration and integration problems (not low-code only) Experience with Power Automate and/or Copilot Studio (or ability to ramp quickly) Practical knowledge of AI pitfalls: hallucinations, prompt brittleness, tool misuse, data quality dependency, governance Nice to Have Microsoft Fabric / Lakehouse exposure; basic data modeling and analytics awareness Experience with SQL Server, MongoDB, Azure DevOps, Graph Databases Experience with AI evaluation/observability tools and practices Familiarity with vector search / knowledge retrieval patterns (e.g., Azure AI Search) Data science experience (helpful, not required) Why You’ll Love Working Here You’ll build foundational AI systems and patterns that shape how Tribe operates High leverage: your work directly reduces operational drag and improves customer experience Small team, real ownership: ship end-to-end and see impact quickly Hybrid flexibility based in Vancouver HQ Generous PTO Powered by JazzHR