AI Implementation Engineer - Vancouver, BC, Canada
1 hour ago
Job description
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.
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
- 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
- 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.
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
- 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)
- 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
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