FacilityOS
AI Engineer
Toronto
Sponsorship not specifiedDetected 9 days ago
OAuthMachine LearningData EngineeringLLMsRAGAgentic AIAI OrchestrationCybersecurityComplianceManual TestingMicrosoft Office
About the role
- The AI Engineer reports to the VP of Engineering and serves as FacilityOS's hands-on technical anchor for AI agent development.
- Evaluate, select, and operate agent orchestration platforms (e.g., OpenClaw or comparable agent orchestration/runtime frameworks) that coordinate multi-step agent workflows, tool calls, and task hand-offs
Responsibilities
- Design, build, and maintain the technical architecture underpinning FacilityOS's AI agents, including RAG pipelines, agent frameworks, and orchestration layers
- Own the organization's approved AI/agent tooling stack in partnership with the VP of Engineering and CTO, evaluating new tools and frameworks as they emerge
- Build and maintain secure authentication and permissioning patterns (e.g., Microsoft Graph API, OAuth) for agents acting inside business systems on a user or department's behalf
- Establish reusable integration patterns for business-system connectivity so each department's agents don't require one-off custom builds
- Build and own the evaluation infrastructure that determines whether an agent actually works - eval harnesses, regression testing for prompts and workflows, and quality/accuracy metrics
- Provide departments with reusable evaluation patterns so they can measure and improve their own agents' quality over time
Requirements
- Experience with agent orchestration platforms or frameworks (e.g., OpenClaw or similar) and integrating agents with business productivity systems such as Microsoft 365, Outlook/email, and Teams is a strong asset
- Working knowledge of data pipelines and structured/unstructured data handling
- Familiarity with security and compliance requirements for enterprise software (SOC2, ISO27001, or similar) is a strong asset
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- Strong experience building production AI/ML systems, with direct experience in agent frameworks, RAG pipelines, or LLM-based applications
- Comfortable working directly with non-technical department stakeholders to translate needs into technical solutions
Nice to have
- Experience in a SaaS or enterprise technology environment preferred
Skills
- Integrate department-selected AI tools and platforms into a consistent, secure, and supportable technical stack
- Hands-on experience integrating APIs, orchestration tools, and third-party AI platforms into production systems
Compensation
- 🎉 Two annual parties in a year
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This listing is sourced directly from FacilityOS's careers page and normalized into a canonical job model.