aimlroles

AI Engineer

FacilityOS facilityos.com Open · verified Oct 22, 2026
Hybrid North York Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at FacilityOS. North York · full-time · CA$120,000–CA$150,000 base.

SalaryStated by FacilityOS
CA$120,000 – CA$150,000
Base salary for this role, in CAD per year, as published in the posting.
RoleAI Engineering
SeniorityMid-level
LocationNorth York
WorkplaceHybrid
EmploymentFull-time
Base payCA$120,000–CA$150,000
PostedJul 13, 2026 · 3mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and maintain the shared technical foundation for department-owned AI agents, from retrieval pipelines to orchestration
  • Connect agents with Microsoft 365, Outlook and Teams using secure, reusable access and integration patterns
  • Test agent prompts and workflows, track quality, and set safeguards against inaccurate or unsafe results
  • Turn department managers’ requirements into working implementations and help resolve technical blockers
  • Prepare deployment-review documentation and maintain security, monitoring and logging standards for agents

What you bring

  • You have built production AI or machine-learning systems, including agent frameworks, retrieval pipelines or LLM applications
  • You have connected APIs, orchestration tools and third-party AI platforms to production systems
  • You can turn non-technical stakeholders’ needs into technical solutions
  • You hold a computer science or engineering degree, or offer equivalent practical experience

Who this fits

This hands-on mid-level role suits an engineer who builds shared infrastructure while departments make decisions about their own agents. The job is hybrid in North York, with in-office work twice a week. You must have legal authorization to work where you applied.

From the employer


About FacilityOS

FacilityOS is a fast-growing company redefining how facilities operate—bringing safety, security, and daily operations into one unified platform used by organizations around the world.

As we continue to scale globally, we’re building a team of driven, curious people who want to make an impact. You’ll be part of a dynamic, collaborative culture where individuals are trusted to take ownership, solve meaningful problems, and grow in their careers. Our team comes together in-office twice a week to connect, collaborate, and build momentum.

If you’re looking to do your best work alongside a great team in a high-growth environment, FacilityOS is the place to build your career.


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. This role sits within the central engineering function that acts as an integrator and enabler for the AI agents that individual departments design and own, building the pipelines, frameworks, and integrations that make department-defined agents production-ready, secure, and scalable.


Department leaders own the discovery, tooling choices, behaviour, and outcomes of their own agents. The AI Engineer's role is to build and maintain the underlying technical architecture, RAG pipelines, agent orchestration platforms, and API integrations into business systems such as Microsoft 365, email, and Teams that supports that department-level ownership, not to run agents on departments' behalf.

Key Responsibilities

Agent Architecture & Development

  • Design, build, and maintain the technical architecture underpinning FacilityOS's AI agents, including RAG pipelines, agent frameworks, and orchestration layers

  • Integrate department-selected AI tools and platforms into a consistent, secure, and supportable technical stack

  • 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

  • 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

Business Systems Integration

  • Connect agents into the core business systems departments already work in - Microsoft 365, Outlook/email, and Teams, so agents can read, draft, notify, and act within existing workflows rather than requiring new interfaces

  • 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

Agent Evaluation & Quality

  • 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

  • Establish guardrails and mitigations for hallucination, unsafe outputs, and failure modes, with clear quality gates an agent must pass before deployment

  • Provide departments with reusable evaluation patterns so they can measure and improve their own agents' quality over time


Cross-Functional Enablement

  • Partner with the Data Engineer to ensure agents have reliable, well-structured data to orchestrate against

  • Act as the technical resource within the AI Tech/Integration SWAT, unblocking department-level technical issues without taking ownership of department agent decisions

  • Translate department managers' agent requirements into working technical implementations

Compliance & Deployment Readiness

  • Build agents to meet FacilityOS's ISO27001 and SOC2 Type 2 compliance requirements from the ground up

  • Prepare technical documentation and evidence required for VP Infosec's mandatory pre-deployment review of every agent build

  • Maintain security, monitoring, and logging standards across all deployed agents

Program Support

  • Provide technical input to the AI Program Lead's portfolio planning, flagging technical risk and feasibility early

  • Support "AI before headcount" evaluations by assessing the technical feasibility of automation before new roles are approved

  • Contribute to org-wide AI-readiness standards and documentation

Qualifications

  • Strong experience building production AI/ML systems, with direct experience in agent frameworks, RAG pipelines, or LLM-based applications

  • Hands-on experience integrating APIs, orchestration tools, and third-party AI platforms into production systems

  • 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

  • Comfortable working directly with non-technical department stakeholders to translate needs into technical solutions

  • Experience in a SaaS or enterprise technology environment preferred

  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Why work at FacilityOS?

We work hard and play hard and we do both with passion and respect for one another. Our company promotes a fast-paced, fun, friendly, and highly collaborative work environment that provides:

🩺Comprehensive health coverage

🏠A Hybrid work environment

💡Opportunity for advancement and growth

🍕 Catered Events, Snacks, Drinks – You won’t go Hungry!

🥳 Birthday and Life Celebrations

🎉 Two annual parties in a year

FacilityOS Commitment

We believe that a diverse team is the key to innovation and growth. We are an equal opportunity employer that value diversity at our company and encourage all candidates to apply. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

FacilityOS will accommodate individuals with disabilities through each stage of the recruitment and selection process. Please advise us of any needs when your interview is booked, and we will do our best to meet your needs.

Please note that all candidates must be legally eligible to work in the location in which you applied.

Background and Reference Checks

Any offer of employment may be conditional upon full background checks including a criminal record check, a credit check and employment and educational verifications. A reference check will also be conducted.

We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications. These tools assist the recruitment team but do not replace human judgment. All advancement and hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us or click here.

FacilityOS thanks all candidates for their interest, however only those selected to continue in the process will be contacted.