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Added just now
EW
Engineering Project Manager II
ERCO Worldwide
Mississauga, ON
- Full-time
Added just now
A
Licensing Engineer
AtkinsRéalis
Mississauga, ON
- Full-time
Candu Energy Inc. is looking to hire a Licensing Engineer for a full-time regular position. This role will provide support to all licensing activities, including interfacing with all…
Added just now
A
Licensing Engineer
AtkinsRéalis
Mississauga, ON
- Full-time
Candu Energy Inc. is looking to hire a Licensing Engineer for a full-time regular position. This role will provide support to all licensing activities, including interfacing with all…
Added just now
A4
Senior QMS / Quality Engineer ( Medical Devices)
Avenue 45
Mississauga, ON
- $110,000 to $145,000 CAD / year
- Full-time
Our direct client is looking for a Senior Quality Engineer / QMS with strong background in Medical Devices, working onsite in Oakville / Mississauga, ON, Canada.
Added just now
G
Senior Engineer, Maintenance
Glencore
Elkford, BC
- $123,000 to $145,000 CAD / year
- Full-time
Reporting to the Senior Supervisor, Engineer the Senior Engineer, Maintenance is responsible
Added 2 mins ago
S
Senior DevOps Engineer – AI & Data Platform
Systematix
Canada
- Contract
We are Systematix and we are currently looking for a Senior DevOps Engineer – AI & Data Platform to help modernize and automate the engineering practices supporting a rapidly growing…
Added 2 mins ago
TT
HVAC engineer
Trane Technologies
Montreal, QC
- Full-time
…truly autonomous buildings. We’re looking for a Mechanical Engineer who brings deep knowledge of HVAC system design, commissioning, and field implementation - someone who understands how…
Added 2 mins ago
AS
Intermediate Technical Support Engineer
Ardent SoftSol Inc.
Toronto, ON
- Contract
Position: Intermediate Technical Support Engineer
Added 2 mins ago
RE
Engineer (Physical AI)
Renesas Electronics
Ottawa, ON
- Full-time
We are seeking an entry level Engineer (Physical AI) to join the Pathfinding Studio within the Engineering Innovation Office. In this role, you will research and develop next generation…
Added 2 mins ago
BC
Senior Manager, Data & AI
BDO Canada
Vancouver, BC
- Full-time
Previous hands-on experience as a technical delivery professional, architect, developer, data engineer, analytics leader, or similar role, with the ability to remain technically credible…
Added 2 mins ago
B
Senior Platform Engineer, AI & Fabrics
BMO
Toronto, ON
- Part-time
You are a hands-on engineer with a strong production track record who takes ownership of your components, cares about operability and correctness, and collaborates well within your team.…
Added 2 mins ago
F
Staff Back End Engineer (Applications)
Forma.ai
Toronto, ON
- Full-time
…customer-facing capabilities. We are seeking a Senior Staff Backend Engineer to join our application teams and help set technical direction across multiple domains within engineering.…
Added 3 mins ago
Senior Specialist, Software Engineering (CI/CD & Automation Engineering)
CMHC - SCHL
Ottawa, ON · Montreal, QC
Added 3 mins ago
SF
Associate Director, Data Engineer
SickKids Foundation
Toronto, ON
- Full-time
We’re committed to attracting and retaining passionate individuals to help create a healthier future. That’s why SickKids Foundation is looking for a new Associate Director, Data Engineer.
Added 15 mins ago
IP
Group Lead, Electrical
IPS-Integrated Project Services
Vaughan, ON
- Full-time
Licensed as a Professional Engineer (P.Eng.) in Ontario, or eligible for licensure with Professional Engineers Ontario, and or any other province or territory in Canada.
Added 15 mins ago
BR
Senior Software Engineer
BITS Recruiting
Toronto, ON
- Contract
Added 15 mins ago
LC
Senior Director, Pharmacy Experience and Transformation
Loblaw Companies Limited
Toronto, ON
- Full-time
Post-Secondary education in Industrial or Process Engineer / Technology / Business/ Healthcare or Operations
Added 15 mins ago
EN
Geotechnical Engineers (Evergreen Talent Pool)
ENGIE North America Inc.
Markham, ON
- Full-time
Licensed and in good standing as a Professional Engineer in Ontario, or able to obtain the required provincial licensure within a timeframe appropriate for the specific position.
Added 17 mins ago
KC
Senior Embedded Software Designer
Kepler Communications Inc.
Toronto, ON
- Full-time
We're on the hunt for a top-tier Senior Embedded Software Engineer. Your focus will be on software development and maintenance required for both space and ground-based assets for a growing…
Added 17 mins ago
MC
DevOps Specialist - Kubernetes (35700)
Myticas Consulting
Ottawa, ON
- Full-time
Added 17 mins ago
G
Technician, Mining
Glencore
Elkford, BC
- $96,000 to $113,000 CAD / year
- Full-time
Reporting to the Senior Engineer Supervisor, Geotech the Mine technician will participate in a variety of tasks, such as: Drone photogrammetric surveys, field layout and interaction with…
Added 18 mins ago
AI Engineer Sr
Dayforce
Canada
We are looking for an AI Engineer - Agentic Systems Evaluation to help define how we measure, test, and improve the quality of enterprise AI systems.
Added 33 mins ago
N
Information Security Engineer (Cloud) - Contract
Numeris
Toronto, ON
- Full-time
Added 46 mins ago
TS
Azure Architect
TECONICA SOFTWARES
Toronto, ON
- Contract
Absolutely. Based on the request in the image, I’d reposition this as a Microsoft Azure Platform Engineer / DevOps Engineer role rather than a Terraform-heavy generic DevOps role.
Added 46 mins ago
AE
Civil Project Engineer
Agnico Eagle Mines Limited
Cochrane, ON
- Full-time
Assist the Senior Civil Project Engineer/Lead with the execution of the capital projects portfolio – Civil discipline support (engineering, procurement & construction);

Levio

Artificial Intelligence Engineer

Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 5, 2026

Original job description

The role

We embed engineers directly inside enterprise clients to find, build, and ship AI and agentic systems that reach production and stay there. A Forward Deployed Engineer runs discovery with the customer's own stakeholders, scopes the use cases worth building, then writes and deploys the working system - in the customer's environment, against their data, under their security and governance constraints.

This is a build-with-the-customer role, not an advisory one. You are the person in the codebase and in the room, closing the gap between an ambiguous "we should use AI" and a governed system operators actually trust and use. You own outcomes through real production usage - you do not hand off a slide deck or a prototype and move on.

What you'll do

Run discovery with the customer's business stakeholders and turn open-ended "we should use AI" asks into scoped use cases, ranked by ROI, data readiness, and technical feasibility.
Build and ship production GenAI and agentic systems end to end - retrieval (RAG), agent orchestration and tool/MCP integration, evaluation harnesses, and the surrounding application and data plumbing.
Deploy inside the customer's environment and constraints: their cloud, their security posture, their data governance - not a sandbox you control.
Design for trust - keep business-critical logic (pricing, rules, calculations) in deterministic code paths, build evaluation and human-in-the-loop review, and know when model output is safe to put in front of operators.
Embed and enable: document the system, run walkthroughs, and lift adoption - while owning the system through real production use, not until the demo.
Present architecture, cost, and delivery trade-offs directly to non-technical decision-makers and keep them bought in.

What we require

You ship code now. Recent, hands-on, first-person production work you can walk through line by line - not architecture you directed or reviewed. If your last real commit was two years ago, this isn't the role.
Real engineering fundamentals. You can drop into an unfamiliar codebase, debug code you didn't write, and build the thing when the platform's GUI can't express it and the AI assistant is stuck. Low-code and AI-assisted development are welcome as tools, not as the whole toolbox.
Genuine customer-facing experience. You've been embedded with customers - in their environment, their mess, their competing priorities - and navigated ambiguity and stakeholders with no direct authority. Internal-only product work doesn't demonstrate this.
Demonstrable production GenAI depth. You've built real RAG and/or agentic systems and can explain the mechanics - retrieval strategy, orchestration, tool-calling - and, above all, how you evaluated them and made them safe to trust. A buzzword list is not depth.
Evaluation and guardrail instinct. You keep the stochastic model out of business-critical decisions, and you can prove your AI output is trustworthy rather than hoping it is.
Verifiable. Code we can look at and claims you can substantiate in a live session. A résumé is a starting point, not evidence.
Ownership temperament. You can own a system through production and iteration, inside a team's codebase and discipline - not only build-and-leave proofs of concept.

Strong pluses

Regulated-industry delivery (financial services, insurance, actuarial, wealth, pension) and comfort with its data, privacy, and governance realities - RBAC, audit, PIPEDA/GDPR.
Governed enterprise-AI patterns: human-in-the-loop, confidence thresholds, audit logging, escalation-path design.
Working depth in one or more of LangGraph or comparable agent frameworks, MCP, and AWS Bedrock / Azure OpenAI / GCP - real depth in one beats a shallow tour of all three.
A track record of taking use cases from discovery to production with measurable, defensible outcomes.
Strong written communication and the ability to teach - enablement is part of the job.

What this role is not

Not an architect or advisory seat. You build and deploy; you don't just diagram, cost, and present.
Not a low-code or platform-configuration role. Platforms are means; the job is engineering.
Not prototype-and-handoff. You own outcomes through production, not until the demo works.
Not a solo BD or fractional-consulting arrangement. This is full-contact delivery on a team.

How we evaluate

We weight what you can demonstrate over what's on the page. Come ready to build, and bring specifics.

A live, assistant-off exercise - extend or debug an unfamiliar codebase in front of us. This is the primary signal.
A production deep-dive - walk us through what broke in production, how you found it, and how you knew your AI output was safe to trust.
A discovery role-play - turn an ambiguous stakeholder ask into a scoped, ROI-ranked use case, out loud.
A depth check on your own claims - pick your strongest AI project and go as deep as we push: the graph, the retrieval, the evals, the guardrails.

Fit check

You'll thrive here if:

You'd rather ship a working system in a customer's messy environment than produce the perfect architecture diagram.
You're energized by ambiguity and being the most accountable person in the room.
You treat "the model said so" as the start of the work, not the end.

This isn't for you if:

You've moved into full-time architecture, strategy, or team leadership and don't miss the code.
Your AI experience is mostly demos, courses, or platform configuration.
You want to advise and hand off rather than build and own.

Apply About employer

More about this job

Responsibilities

Lead customer discovery to identify and prioritize AI use cases, then build, deploy, and maintain production GenAI and agentic systems within customer environments and governance constraints. Design evaluations and safeguards, support adoption through documentation and enablement, and communicate technical and delivery trade-offs to decision-makers.

Requirements

Requires recent, hands-on production coding experience, strong engineering and debugging fundamentals, customer-facing delivery experience, and demonstrable depth building and evaluating RAG or agentic systems. Candidates must be able to design trustworthy guardrails, own systems through production iteration, and substantiate their work in practical assessments.

Skills

Production GenAI Engineering
Retrieval-Augmented Generation (RAG)
Agent Orchestration
Tool and MCP Integration
Evaluation Harnesses
Software Engineering
Customer Discovery
Production Deployment
Cloud Platforms
Data Governance
Security and Privacy
Human-in-the-Loop Review
Guardrail Design
Stakeholder Communication
Debugging
System Ownership

Visa sponsorship

Not detected in the job text

Keywords

Generative AI
Agentic Systems
Retrieval-Augmented Generation (RAG)
Agent Orchestration
Tool Calling
Model Context Protocol (MCP)
LangGraph
AWS Bedrock
Azure OpenAI
Google Cloud Platform
Evaluation Harnesses
Human-in-the-Loop
Confidence Thresholds
Audit Logging
Escalation Paths
Cloud Deployment
Data Governance
Role-Based Access Control (RBAC)
PIPEDA
GDPR
Regulated Industries
Production Engineering
Customer Discovery
ROI Prioritization
Security and Privacy
Deterministic Business Logic
Enterprise AI
System Evaluation
Production Monitoring

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