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Added 1 month ago
E
Lead Full Stack Engineer
eBay
Toronto, ON
- Full-time
Proven system design expertise with distributed systems, including scalability, reliability, and performance trade-offs.
Added 5 months ago
C
Staff Chip Design Engineer - FPGA
Cognichip
Toronto, Ontario
- $184,000 to $222,000 CAD / year
- Full-time
At Cognichip, we’re not just building AI - we’re redefining what’s possible at the nexus of silicon design and machine learning. As a Staff FPGA Design Engineer, you will fuse chip design…
Added 6 months ago
LI
Artificial Intelligence Engineer
LanceSoft, Inc.
Montreal, Quebec
- Contract
Design reviews, ADRs, ICAG-style governance forums
Added 6 months ago
TA
Senior Machine Learning Engineer (GCP)
Tiger Analytics
Canada
- Full-time
Tiger Analytics is looking for a skilled and innovative Machine Learning Engineer with hands-on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable…
Added 6 months ago
F
Computer Vision & Behavioral Signal Analysis Intern (Healthcare Focus)
FairwAI
Remote, Canada
- Remote
…Engineering, B.S. in Physics, M.S. in Electrical Engineering, an Engineer’s Degree, and a Ph.D. in Electrical Engineering. He earned the David Adler Memorial Thesis Prize and the Morris…
Added 3 months ago
F
AI Engineer
FacilityOS
Remote, Canada
- $120,000 to $150,000 CAD / year
- Full-time
- Remote
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…
Added 1 month ago
T
Senior Software Engineer (Back-end/Server)
Trulioo
Vancouver, BC · Toronto, ON
- Full-time
Trulioo is looking for a Senior Software Engineer to lead the architecture and development of high-throughput, low-latency back-end services that power our Document and Biometric…
Added 6 months ago
H
Senior Software Engineer, Data
Hive
Remote, Canada
- $123,600 to $187,900 USD / year
- Full-time
- Remote
…scale. We aren’t focused on only BI or dashboards - we build the systems that power Hive’s products and make data accessible, reliable, and…
Added 6 months ago
S
Software Engineer - Solutions
Suger
Vancouver, British Columbia
- $90,000 to $130,000 CAD / year
- Full-time
…position. You’ll work with the engineering and product teams to design, build, and launch complex integrations on top of Suger’s platform, while also shaping internal systems, APIs, and…
Added 6 months ago
S
Software Engineer - Solutions (Marketplace & AI Integrations)
Suger
Vancouver, British Columbia
- $90,000 to $130,000 CAD / year
- Full-time
…pre-sales position. You’ll partner with engineering teams to design, build, and launch complex integrations on top of Suger’s platform, while also shaping internal systems, APIs, and…
Added 6 months ago
K
Senior Software Engineer, AI
Klue
Toronto, Ontario
- $145,000 to $183,000 CAD / year
- Full-time
We're looking for a Senior Software Engineer to join our team in Toronto, focusing on building and optimizing state-of-the-art LLM-powered agents that can reason, plan and automate…
Added 6 months ago
K
Senior Software Engineer, AI (Agents)
Klue
Vancouver, British Columbia
- $145,000 to $183,000 CAD / year
- Full-time
Build and ship backend systems that power agentic workflows. You design retrieval pipelines, orchestration layers, and multi-step agent architectures that turn millions of competitive data…
Added 6 months ago
JC
Machine Learning Engineer - IV (Biometrics)
Jumio Corporation
Montreal, Quebec
- Full-time
We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production.…
Added 1 month ago
C
Senior Test Automation Engineer – AI Testing
Cognizant
Montreal, QC
- Full-time
Added 6 months ago
F
Full Stack Engineer, Early Career
Feathery
Toronto, Ontario
- Full-time
We’re hiring a Full Stack Engineer to help build and scale core product capabilities end-to-end. This role is ideal for someone early in their career who enjoys owning features across the…
Added 6 months ago
HC
Senior Principal Researcher & Technical Leader – Agentic RL for Distributed Computing
Huawei Canada
Markham, Ontario
- Full-time
Solid foundations in optimization, probability, and game theory, with the ability to design and analyze complex learning systems.
Added 6 months ago
G
Senior Infrastructure Engineer
Gumloop
Vancouver, British Columbia
- $200,000 to $300,000 USD / year
- Full-time
We're looking for a Senior Infrastructure Engineer to own and scale the systems that power Gumloop. You'll architect and roll out large-scale infrastructure projects independently, define…
Added 3 months ago
EG
Sr. Data Platform Engineer
Etraveli Group
Toronto, Ontario
- Full-time
Design StatefulSet, PVC, pod-disruption-budget, and rolling-upgrade patterns that are safe for production data systems.
Added 3 months ago
FA
Software Engineer - Data
Forum Asset Management
Toronto, Ontario
- Full-time
We’re looking for a Software Engineer - Data to design, build, and evolve Forum’s next-generation enterprise data platform using the Microsoft Fabric technology stack (or a suitable…
Added 1 month ago
Staff Machine Learning Engineer
OpenTable
Toronto, ON
As a Staff Machine Learning Engineer, you will set the technical direction for how OpenTable builds, serves, and operates machine learning systems in production. You will partner with…
Added 3 months ago
M
{NEW} Applied AI, Technical Lead, Forward Deployed AI Engineer
Mistral
Montreal, Quebec
- Full-time
- Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap…
Added 3 months ago
TH
Senior AI Engineer - Full time
Trillium Health Partners
Mississauga, Ontario
- Full-time
Reporting to the Director, AI & Digital Planning, the Senior AI Engineer will be responsible for using the latest AI tools to design, prototype, build, evaluate, and scale AI solutions…
Added 3 months ago
CF
Senior AI Engineer
CI Financial
Toronto, Ontario
- Full-time
Design, prototype, and lead development of agentic AI systems capable of multi-step reasoning, task decomposition, and tool use to automate and support complex business workflows.
Added 1 month ago
R
Principal Data Science and AI Engineer
RBC
Toronto, ON
- Full-time
As a Principal AI Engineer, you will be at the helm of developing, deploying, and owning the strategic direction of advanced AI systems, including autonomous AI agents that leverage and…
Added 1 month ago
RB
Generative AI Data Scientist & ML Engineer
Royal Bank of Canada
Toronto, ON
- Full-time
…including the creation of efficient indexing and retrieval systems, to enhance the organization's ability to quickly and accurately access relevant…

FacilityOS

AI Engineer

Remote, Canada

Remote

$120,000 to $150,000 CAD / year · Full-time

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Job details

Pay: $120,000 to $150,000 CAD / year
Job type: Full-time
Workplace: Remote
Posting language: English
Posted: Jul 13, 2026

Original job description

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.

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More about this job

Responsibilities

The AI Engineer designs and maintains the technical architecture for AI agents, including RAG pipelines and orchestration layers. They integrate these agents into business systems like Microsoft 365 and establish evaluation frameworks to ensure quality and security.

Requirements

Candidates need strong experience building production AI/ML systems and integrating APIs into enterprise environments. A bachelor's degree in Computer Science or Engineering is preferred, along with familiarity with SOC2 and ISO27001 compliance.

Skills

AI Agent Development
RAG Pipelines
LLM Applications
API Integration
Agent Orchestration
Microsoft Graph API
OAuth
Evaluation Infrastructure
Data Pipeline Management
SOC2 Compliance
ISO27001 Compliance
Technical Architecture Design
SaaS Development
Prompt Engineering
Regression Testing
Cross-functional Collaboration

Benefits

Comprehensive health coverage
Hybrid work environment
Opportunity for advancement and growth
Catered events
Snacks
Drinks
Birthday and life celebrations
Two annual parties

Visa sponsorship

Not detected in the job text

Keywords

AI Engineer
RAG
LLM
OpenClaw
Microsoft 365
Outlook
Teams
Microsoft Graph API
OAuth
SOC2
ISO27001
SaaS
Agent Orchestration
Enterprise Technology
Data Pipelines
Evaluation Harnesses
Hallucination Mitigation
Technical Architecture
API Integration
Production AI

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