Jobs in Canada

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Added 1 month ago
ED
Senior Quality Engineer/Lead - EN 323
Export Development Canada | Exportation et développement Canada
Ottawa, ON
- $96,557 to $128,743 CAD / year
- Full-time
Senior Software Engineer 18: Salaries typically range from $96,557 to $128,743 annually, based on qualifications and experience plus a performance-based incentive of 15%
Added 1 month ago
A
Senior AI Platform Engineer (MLOps)
Akkodis
Toronto, ON
- Contract
Work Model: Hybrid (Downtown Toronto - 3 days in office)
Added 1 month ago
A
Senior Software Engineer - GPU Profiling Tools
AMD
Markham, ON
- $132,000 to $198,000 CAD / year
- Full-time
AMD is looking for a Senior Software Engineer - GPU Profiling Tools for the Developer Tools team, where you will contribute to the development and optimization of GPU profiling tools for…
Added 1 month ago
T
Data Engineer II
TD
Toronto, ON
- Full-time
Added 1 month ago
SL
Engineering Manager
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Waterloo King
- Full-time
Flexible Workstyle: In office 2-3 days per week, hybrid the rest of the week
Added 1 month ago
Senior Analytics Engineer
Aviva
Markham, ON
Added 1 month ago
MI
Mould Maker
Magna International
Tecumseh, ON
- Full-time
Interact with Process Engineer, Quality Assurance, Manufacturing and Maintenance
Added 1 month ago
FF
Principal Software Engineer
Forward Financing
Remote, Canada
- $200,000 to $250,000 CAD / year
- Full-time
- Remote
…analytical capabilities. We’re seeking a seasoned Principal Engineer with an architect’s mindset to own the technical vision and execution. As a technical leader, you will be instrumental…
Added 1 month ago
L
Artificial Intelligence Engineer
Levio
Canada
- Full-time
…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…
Added 1 month ago
S
AI Workflow & Operations Intern
Semtech
Richmond, BC
- Full-time
…and making them work better. You don’t need to be a software engineer - but you do need to be comfortable with data, curious about AI, and motivated by operational impact. If you’ve ever…
Added 1 month ago
Structure Design Engineer
Infosys
Quebec, QC
Added 1 month ago
CL
Senior Okta Engineer (IAM)
Charger Logistics Inc.
Brampton, ON
- Full-time
Senior Okta Engineer (IAM) - Non-Human & AI Agent Identity
Added 1 month ago
L
Principal Mechanical Designer (Minerals Plant Layout)
Lycopodium
Vancouver, BC
- Full-time
…supervision of the Principal Designer, Lead Discipline Design Engineer or the Project Lead…
Added 1 month ago
ED
Senior Quality Engineer/Lead - EN 323
Export Development Canada | Exportation et développement Canada
Remote, Canada
- Full-time
- Remote
Senior Software Engineer 18: Salaries typically range from $96,557 to $128,743 annually, based on qualifications and experience plus a performance-based incentive of 15%
Added 1 month ago
RB
Staff AI Architect/Engineer
Royal Bank of Canada
Toronto, ON
- Full-time
This is a tremendous opportunity to reinvent architecture in the AI Age. As a Staff AI Architect/Engineer, you will operate at the intersection of hands-on AI building and enterprise…
Added 1 month ago
Z
Senior Software Developer
Zynga
Toronto, ON
- $99,800 to $147,680 CAD / year
…work in a team with dynamic strengths. The Senior Software Engineer will be working with a complementary team of software engineers to craft and maintain Zynga’s core Payments platform,…
Added 1 month ago
Staff Information Security Engineer - Threat Detection & Response
Visier Solutions Inc
Vancouver, BC
Added 1 month ago
EM
AI Solutions Lead
EC Managed IT
Langley (District), BC · Langley, BC
- Full-time
…helping those teams adopt the change. You are not a software engineer and you will not manage people. You are the person who can walk into an office, understand how the work actually gets…
Added 1 month ago
CI
Geotechnical Engineer/Project Manager
Cambium Inc.
Barrie, ON · Whitby, ON
- Full-time
Registered Professional Engineer (P.Eng.) in Ontario, or eligible to obtain registration in near term.
Added 1 month ago
C
Senior Java Engineering Lead
Citi
Mississauga, ON
- Full-time
As a Senior Backend Java Engineer, you will design and build scalable backend systems that power critical applications within Citi's technology organization. This hands-on role puts you at…
Added 1 month ago
Senior Okta Engineer (IAM)
Charger Logistics Inc
Brampton, ON
Senior Okta Engineer (IAM) – Non-Human & AI Agent Identity
Added 1 month ago
GM
Principal Software Engineering - Test System Modernization
General Motors
Markham, ON
- Full-time
General Motors is seeking a Principal/Staff Software Engineer to shape and scale the engineering platforms that build, test, integrate, validate, and deliver embedded software for…
Added 1 month ago
H
Senior Test & Validation Engineer
Humanoid
Burnaby, BC
- Full-time
As a Senior Test and Validation Engineer at Humanoid, you will be responsible for bringing new hardware subsystems into a functional, controllable, measurable, and integration-ready state,…
Added 1 month ago
Senior Software Engineer, Security Engineering - Platform (Auth0)
Okta
Toronto, ON
Senior Software Engineer, Security Engineering
Added 1 month ago
H
Sales Engineer, Eastern Canada
Horizon3
Remote, Canada
- Full-time
- Remote
We’re looking for a Sales Engineer to partner closely with our Account Executives and help growing organizations understand the technical and business value of our platform. This role is…

Levio

Artificial Intelligence Engineer

Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

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 on LinkedIn 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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Work requirements

Jobs in Canada