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Added 12 mins ago
NG
Desktop Support Engineer (Level 2)
NSC Global
Brantford, ON
- Other
…peripherals. Documents, maintains, upgrades or replaces hardware and software systems. Supports and maintains user account information including rights, security and systems groups. May…
Added 12 mins ago
M
Senior DevOps Engineer
Miovision
Remote, Canada
- $130,000 to $170,000 CAD / year
- Full-time
- Remote
We are currently looking for a Senior DevOps Engineer to contribute to the development of our cloud infrastructure and platform tooling, embed security into our engineering lifecycle, and…
Added 27 mins ago
L
Senior Forward Deployment Engineer
Luxoft
Mississauga, ON
- Full-time
The role combines senior software engineering, DevOps, SRE, test automation, application security, and legacy modernization. Approximately 70% of the work involves hands-on coding and…
Added 27 mins ago
S
Software Engineer
Syntrace
Vancouver, BC
- Full-time
We are now hiring a Software Engineer, based in Vancouver.
Added 28 mins ago
Technology Lead
Infosys
ON
Deep knowledge of cloud storage, networking basics, IAM, and security best practices.
Added 28 mins ago
SM
Trust & Safety Engineer - Hapiko
Spin Master
Toronto, ON
- Full-time
…core of the product. As our first dedicated Trust & Safety engineer, you'll own the systems that keep it that way as we…
Added 57 mins ago
EI
Technical Program Manager
EMERES INC.
Montreal, QC
- Full-time
Prior experience as a software engineer or QA engineer
Added 58 mins ago
VC
Développeur fiscal - Ingénieur de données | Tax Developer - Data Engineer
Valsoft Corporation
Montreal, QC · Saint-Laurent, Quebec
- Full-time
Valsoft is looking for a Data Analytics Engineer to join our Tax department in Montreal, Quebec, working closely with Tax, Finance, Data Platform teams, and external consultants to build…
Added 1 hour ago
B
Technical Specialist II
BMO
Toronto, ON · SCC
- Full-time
We are looking for a highly skilled DevOps/Site Reliability Engineer (SRE) to join one of our high-performing, mission-critical technology teams. This role offers the opportunity to work on…
Added 1 hour ago
A
Senior Machine Learning Engineer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
- Full-time
We are looking for an exceptional Machine Learning Engineer to design, build, operationalize, and scale production-grade AI/ML and Agentic AI systems at Autodesk For Go-to-market…
Added 1 hour ago
KG
Enterprise Security Architect - Senior Security Engineer
K&K Global Talent Solutions INC.
Toronto, ON
- Full-time
Role : Enterprise Security Architect - Senior Security Engineer
Added 1 hour ago
D
Senior Product Engineer II - Backend
Docebo
Toronto, ON
- $123,400 to $164,500 CAD / year
- Full-time
As a Senior Product Engineer II, you bring deep expertise in backend engineering alongside strong working competency across the broader stack. You own complex features and technical…
Added 1 hour ago
AA
Software Verification Engineer
Aviya Aerospace Systems
Mississauga, ON
- $67,000 to $97,000 CAD / year
- Full-time
…applications. Aviya provides expertise in program management, systems, software, mechanical, and hardware engineering to many of the top-tier Aerospace and Defense Contractors. We have…
Added 1 hour ago
Dev Ops Engineer (Student Position)
The Canada Life Assurance Company
Winnipeg, MB · London, ON · Toronto, ON
We are looking for a DevOps Engineer Student who is interested in learning how modern technology platforms are built, delivered, and supported within a large enterprise environment.
Added 1 hour ago
Forward Deployed Engineer, Application & Infrastructure - Technology Strategy & Transformation
EY
Toronto, ON
Build and improve CI/CD pipelines, automated testing, security scanning, release processes, and software-delivery controls.
Added 1 hour ago
Forward Deployed Engineer, AI - Technology Strategy & Transformation
EY
Toronto, ON
1-5 years of experience in AI engineering, software engineering, application development, technology consulting, or related delivery roles, including relevant co-op or internship experience.
Added 1 hour ago
Stationary Engineer - Class 4B
Recrute Action
Longueuil, QC
Investigate situations that may affect the safety and security of facilities and personnel.
Added 1 hour ago
Q
Power Systems Engineer III
Qualus
Bolton, ON
- Full-time
Power your future with Qualus as a Power Systems Engineer III. The Engineer III is responsible for providing technical and engineering support for field work, and office work performing…
Added 1 hour ago
Digital Engineer
Alstom
Saint-Bruno, QC
Could you be the full-time Digital Engineer in Saint Bruno we’re looking for?
Added 2 hours ago
A
Intermediate Instrumentation Control and Electrical Engineer
AtkinsRéalis
Mississauga, ON
- Full-time
This position is ideal for an engineer who enjoys combining electrical design, instrumentation, automation, software development, testing, and hands-on field execution while contributing to…
Added 2 hours ago
R
Software Engineer
RBC
Toronto, ON
- Full-time
Provide technical leadership and mentorship, ensuring adherence to best practices, security standards, and performance benchmarks
Added 2 hours 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 2 hours ago
CE
Network Engineer
Capgemini Engineering
Toronto, ON
- Full-time
…From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join…
Added 2 hours ago
MC
Platform Engineer - Azure (35991)
Myticas Consulting
Canada
- Contract
Experience in regulated or security-conscious environments is an asset.
Added 2 hours ago
EI
QUALITY & PROCESS LEAD
EMERES INC.
Montreal, QC
- Full-time
Lead and grow the QA engineering function, including QA Engineers/SDETs (Software Development Engineer in Test).

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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