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Added 8 mins ago
T
Quality Engineer II (VMS)
TD
Toronto, ON
- Full-time
Effectively engineer and leverage tools and Engineering practices (DevOps tools and processes, source code management, Service Virtualization, monitoring tools, etc.)
Added 1 hour ago
B&
Lead, AI Engineering
Bain & Company
Zurich, ON
- Full-time
As an AI Engineer in AIS, you will build the technical core of these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The…
Added 2 hours ago
SM
AI Engineer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking a position of AI Engineer role for Citi based in Mississauga, ON, Canada. The role focuses on designing, building, and deploying Python-based AI/LLM applications and scalable…
Added 2 hours ago
SM
AI Engineer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking a position of AI Engineer role for Citi based in Mississauga, ON, Canada. The role focuses on designing, building, and deploying Python-based AI/LLM applications and scalable…
Added 2 hours ago
SM
AI Engineer
S M Software Solutions Inc
Mississauga, ON
- Full-time
We are seeking a position of AI Engineer role for Citi based in Mississauga, ON, Canada. The role focuses on designing, building, and deploying Python-based AI/LLM applications and scalable…
Added 2 hours ago
M
Senior Software Engineer - Card Network Integration
Marqeta
Remote, Canada
- Full-time
- Remote
Marqeta is seeking a skilled Senior Software Engineer to join the Network File Integration team. In this role, you will help design and deliver scalable software solutions for batch and…
Added 2 hours ago
E
Ingénieur(e) En Gestion De Données ML
Ericsson
Montreal, QC
- Full-time
Added 3 hours ago
AI
Kubernetes Engineer
Aptino, Inc.
Canada
- Contract
We are looking for an experienced Kubernetes (K8S) / HPC Engineer to design, deploy, and manage scalable compute platforms supporting AI/ML, simulation, and data-intensive workloads.
Added 3 hours ago
B
Software Engineer- Inference Performance
Baseten
Montreal, QC
- $180,000 to $360,000 USD / year
- Full-time
You'll get to work on these types of projects as an Inference Performance engineer:
Added 4 hours ago
J
Python Engineer, New Grad
Jobright.ai
Canada
- Full-time
…accelerating your route to the best job outcomes. As a Python Engineer, New Grad, you will contribute to backend services, data pipelines, APIs, and AI-powered workflows used by real job…
Added 4 hours ago
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Software Engineer – Master’s New Grad / Bachelor’s + 2–3 Years Experience
Nutanix
Vancouver, BC
- $103,000 to $155,000 CAD / year
- Full-time
Are you an enthusiastic early-career engineer passionate about building secure AI infrastructure from the ground up? Join Nutanix to help develop our DataHub platform - an enterprise data…
Added 4 hours ago
PU
Staff Software Engineer – Data Systems
Purpose Unlimited
Remote, Canada
- Full-time
- Remote
Purpose Unlimited is building the financial products infrastructure that puts clients first, and we need the engineer who ensures that infrastructure is fast, reliable, and built to evolve.…
Added 4 hours ago
AM
AI Fleet Management Solutions
Advanced Micro Devices, Inc
Markham, ON
- Full-time
AMD is looking for an AI solutions systems Engineer who is passionate about complex and innovative AI solutions, AI infrastructure, fleet management and automation solutions. You will be a…
Added 4 hours ago
AM
Senior Software Engineer - GPU Profiling Tools
Advanced Micro Devices, Inc
Markham, ON
- 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 5 hours ago
Software Engineer
Apple
Vancouver, BC
Added 6 hours ago
ET
Senior LLM Research Engineer
Encore Technical Solutions Inc.
Toronto, ON
- Full-time
We're looking for a Senior LLM Research Engineer to help build and optimize advanced language models for complex, real-world applications. This role spans the full lifecycle of model…
Added 6 hours ago
Systems Engineer, Data Center Debug
Tenstorrent
Toronto, ON
Hands-on engineer who excels at diagnosing complex hardware, firmware, and software issues through root-cause analysis.
Added 6 hours ago
CI
Intern Analyst, PhD – Systematic Strategies Group
CPP Investments | Investissements RPC
Toronto, ON
- Full-time
…tools using macroeconomic, market and alternative datasets, engineer robust data workflows, and help translate academic research into enhancements to investment…
Added 6 hours ago
P
Sr. Fuil Stack Engineer, Threat Intelligence
Proofpoint
ON · Ontario, Canada
- Full-time
Added 6 hours ago
IW
AI Development & Continuous Improvement Student (Summer 2027)
Irving Woodlands
Saint John, NB
- Full-time
Reporting to the Maintenance Process & Performance Engineer, the role will support the development and implementation of digital solutions that improve operational efficiency, automate…
Added 6 hours ago
AI
AWS DATA ENGINNER
Apptoza Inc.
Toronto, ON
- Contract
As a senior technical leader, you will collaborate with architecture, analytics, and business teams to define long-term data strategy, establish engineering best practices, and support…
Added 6 hours ago
P
Sr. Fuil Stack Engineer, Threat Intelligence
Proofpoint
Quebec, QC
- Full-time
Added 6 hours ago
RT
Engineer Enterprise Asset Management
Rio Tinto
Kitimat, BC
- Full-time
We are looking for an Engineer to support the design, governance and continuous improvement of asset master data across our maintenance systems. In this role, you will apply engineering…
Added 6 hours ago
G
Senior AI Engineer
Guidepoint
Toronto, ON
- Full-time
You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad…
Added 6 hours ago
AI
JAMS Platform Engineer
Apptoza Inc.
Toronto, ON
- Contract
Seeking a hands-on engineer to drive the reliability| automation and modernization of the enterprise JAMS workload automation platform. The role combines JAMS platform expertise with…

Levio

Artificial Intelligence Engineer

Canada

Full-time

Apply About employer

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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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