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Added 1 hour ago
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Database Platform Engineer
AppDirect
Montreal, QC
- Full-time
We are looking for a Database Platform Engineer to join our Data Platform team. You are a highly technical professional with an entrepreneurial spirit and a data-as-a-service mindset. You…
Added 1 hour ago
PT
Software Engineer
Purelend Technologies Inc.
Calgary, AB
- Full-time
We're hiring a Software Engineer to join our core product team and own meaningful chunks of the platform end-to-end. This isn't a role where you get handed a Jira ticket and a fully-specced…
Added 1 hour ago
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AI Engineer, Entry Level (Canada)
Jobright.ai
Canada
- Full-time
…the job search experience. They are seeking an entry-level AI Engineer to build and refine autonomous AI agents, develop sophisticated prompt engineering workflows, and integrate Large…
Added 1 hour 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 1 hour ago
J
Prompt Engineer - Early Career (Canada)
Jobright.ai
Canada
- Full-time
…job search process. They are seeking an early-career Prompt Engineer to craft and evaluate prompts that enhance the performance of AI outputs across user-facing…
Added 3 hours ago
MW
Backend Engineer (Golang)
Mai Wealth
Engineer, BC
- Full-time
Added 3 hours ago
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AI Engineer
maru.ai
Engineer, BC
- Full-time
We are an early stage startup developing cutting-edge AI technology. We are looking for a talented AI engineer to join our small but growing team. You will have the opportunity to take on a…
Added 3 hours ago
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Software QA Engineer
maru.ai
Engineer, BC
- Full-time
We are looking for a detail-oriented Software QA Engineer to join our fast-growing AI/ML startup. In this role, you will help ensure the quality of our AI/ML products by designing and…
Added 3 hours ago
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Software Engineer
maru.ai
Engineer, BC
- Full-time
Added 3 hours ago
BS
ML/AI Engineer
Brock Software
Engineer, BC
- Full-time
We're seeking an experienced engineer to fine-tune open source models, train them on custom datasets, and deploy them to production using GPU infrastructure on platforms like fly.io.
Added 3 hours ago
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Machine Learning Engineer Intern
Jobright.ai
Canada
- Internship
…helps users reach better job outcomes. The Machine Learning Engineer Intern will develop and evaluate machine-learning features, support data pipelines and integrations, investigate model…
Added 4 hours ago
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Manager, Software Engineering
AltaML
Toronto, ON
- Full-time
We overpay for the right people. We'd rather pay a premium for an engineer who embodies this and multiplies the team than save money on someone who doesn't.
Added 4 hours ago
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Intermediate Software Engineer
AltaML
Toronto, ON
- $90,000 to $110,000 CAD / year
- Full-time
We overpay for the right people. We'd rather pay a premium for an engineer who embodies this and multiplies the team than save money on someone who doesn't
Added 4 hours ago
RR
Hardware Test Engineer
Remote Robotic
Ottawa, ON · Kanata, ON
- $82,000 to $100,000 CAD / year
- Full-time
AirMetal is looking for a Test Engineer, FPV Electronics to develop the systems that validate the performance, reliability, and quality of our FPV and uncrewed-aircraft electronics.
Added 4 hours ago
SI
Forward Deployed Engineer
SPERTON India - Where Great People Meet
Canada
- Full-time
You’ll be expected to operate like an engineer, product manager and technical operator at the same time - understanding the business problem, deciding what should be built, shipping it, and…
Added 4 hours ago
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Principal Product Manager - Identity Threat Detection and Response
Elastic
Canada
- Full-time
…You are an advocate for the security analyst and detection engineer, and you are focused…
Added 5 hours ago
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Security Engineer II - Identity and Access Management
Marqeta
Remote, Canada
- Full-time
- Remote
We’re seeking an experienced Security Engineer II with a strong passion for Identity and Access Management (IAM) and expertise in cloud-native environments, particularly AWS. You'll build,…
Added 5 hours ago
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Senior Bridge Engineer
Jacobs
Ottawa, ON
- $160,000 to $210,000 USD / year
- Full-time
…and design assignments and is the #2 Bridge firm as ranked by Engineer News Record. We are looking for a highly motivated and personable Senior Bridge Engineer based in…
Added 5 hours ago
Director, Water and Wastewater Infrastructure Management
Region of Waterloo
Kitchener, ON
Added 6 hours ago
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Technician, MiningNew
Glencore Canada
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 6 hours ago
GC
Senior Engineer, MaintenanceNew
Glencore Canada
Elkford, BC
- $123,000 to $145,000 CAD / year
- Full-time
Reporting to the Senior Supervisor, Engineer the Senior Engineer, Maintenance is responsible
Added 6 hours ago
HR
Software Analyst
Hitachi Rail
Toronto, ON
- Full-time
Added 6 hours ago
HR
Software Analyst
Hitachi Rail
Toronto, ON
- Full-time
Added 7 hours ago
SC
Utilities Engineer – Interface Management (Intermediate)
SYSTRA Canada
Toronto, ON
- Full-time
The Utilities Engineer – Coordination and Interface Management is responsible for the identification, coordination, and resolution of interfaces between the High-Speed Rail (HSR) project…
Added 7 hours ago
C
Building Operator
CBRE
Vancouver, BC
- Full-time
4th Class Power Engineer; or willing to obtain within 6 months of hire

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.

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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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