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Architect - Azure/Terraform- Cloud Platform Engineer
TECONICA SOFTWARES
Toronto, ON
- Contract
We are seeking a highly hands-on Azure Platform Engineer with strong experience designing, implementing, and supporting enterprise-scale Microsoft Azure cloud platforms.
Added just now
GS
Artificial Intelligence Engineer
Gala Solutions
Montreal, QC
- Contract
…on any combination of the following platforms - Kubernetes, cloud (AWS, Azure, and/or Google), API-based development, REST framework, data engineering, large-scale API gateway environments,…
Added 31 mins ago
SG
Senior Solution Designer
SRA Group
NB · New Brunswick, Canada
- $85 to $90 CAD / hour
- Contract
…candidate will possess deep expertise in Microsoft Fabric, Azure Synapse Analytics, and modern cloud data platforms, with a proven track record of designing and delivering enterprise-scale…
Added 33 mins ago
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Lead Data Engineer
ZS
Toronto, ON
- Full-time
Strong understanding of data warehousing concepts and cloud-based data platforms (e.g., AWS, Azure, GCP).
Added 35 mins ago
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Principal Cloud Engineer
BMO
Toronto, ON · BMOPLACE
- Full-time
We are seeking an enthusiastic, passionate professional for a Principal Cloud Engineer position with 8+ years of experience in multiple large scale Azure enterprise environments. We are…
Added 35 mins ago
M
Full-Stack Software Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
…maintainable solutions using C#, .NET, F#, React, microservices, and Azure Kubernetes Service (AKS). This role offers the opportunity to work with complex business and calculation logic,…
Added 1 hour ago
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SnapLogic Support Engineer
W3Global
Canada
- Contract
We are seeking a SnapLogic Support Engineer to provide production support, monitoring, troubleshooting, and maintenance of enterprise integrations built on the SnapLogic platform. The role…
Added 1 hour ago
A
Information Technology - Lead Analytics Engineer, Distribution Technology
Aritzia
Vancouver, BC
- Full-time
…This is a unique opportunity to transform raw data in a modern platform and create models that empower self-serve analysis, reporting, and data science. As the Lead Analytics Engineer, you…
Added 1 hour ago
FT
Lead Software Engineer
Franklin Templeton
Toronto, ON
- Full-time
Operating Environment: Cloud-based (Azure + Snowflake ecosystem)
Added 1 hour ago
M
Senior Full Stack Engineer, Customer & Cardholder Experiences
Marqeta
Remote, Canada
- Full-time
- Remote
Experience developing scalable microservices on cloud platforms like AWS (preferred), Azure, or GCP
Added 3 hours ago
Y
Site Reliability Engineer
Yochana
Toronto, ON
- Contract
Collaborate with engineering, cloud, and security teams to improve platform resiliency.
Added 3 hours ago
KC
Site Reliability Engineer
KPMG Canada
Vaughan, ON
- Full-time
The OPS Site Reliability Engineer will be a focal role owning and ensuring the fluent operations of Managed Services offerings in the KPMG production cloud environment. The role will be…
Added 3 hours ago
DI
Senior IT Security Engineer
Draganfly Inc.
Burnaby, BC
- $120,000 to $140,000 CAD / year
- Full-time
The Senior IT Security Engineer builds, operates, and improves security across Draganfly’s cloud-first IT environment. This hands-on role combines Microsoft 365 and cloud security…
Added 3 hours ago
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Senior Software Engineer - Trading Technology
BettingJobs
Toronto, ON
- Full-time
BettingJobs is working with a fast-growing sports betting technology business to recruit a Senior Software Engineer for its Trading Technology team. You'll build the backend engines behind…
Added 3 hours ago
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Senior Data Engineer
TekRek
Montreal, QC
- $140,000 to $160,000 CAD / year
- Full-time
As a Senior Data Engineer, you'll own data platform design and delivery for client engagements, from scoping and architecture through to production. You'll work directly with client…
Added 3 hours ago
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Senior Data Engineer || Ottawa/Toronto || Local only
TestingXperts
Toronto, ON
- Contract
· Previous experience leading an enterprise-wide Cloud Data Platform migration with strong architectural and design skills.
Added 4 hours ago
BC
Senior Manager, Data & AI
BDO Canada
Vancouver, BC
- Full-time
Experience with modern Data & AI technologies such as Microsoft Fabric, Azure Databricks, Snowflake, dbt, Power BI, Microsoft Purview, Azure Data Factory, Azure Synapse, Azure Machine…
Added 4 hours ago
R&
Senior Azure Cloud Platform Engineer
Robertson & Company Ltd.
Toronto, ON
- Contract
Robertson is seeking a skilled Senior Azure Cloud Platform Engineer to join our client in support of an existing vacancy.
Added 4 hours ago
CS
Java developer
Cyber Space Technologies LLC
Montreal, QC
- Full-time
Knowledge of cloud platforms (AWS, Azure, or GCP).
Added 4 hours ago
N
Senior Cloud Systems Engineer (CI/CD & Data Platform)
Numeris
Toronto, ON
- Full-time
Numeris is seeking a Senior Cloud Systems Engineer to lead the design, automation, and operation of enterprise cloud platforms across AWS and Azure. This role combines deep expertise in…
Added 4 hours ago
N
Enterprise Cloud & Platform Engineer
Numeris
Toronto, ON
- Full-time
The Enterprise Cloud & Platform Engineer is responsible for the design, implementation, administration, continuous improvement, security, and operation of enterprise cloud, network,…
Added 4 hours ago
AS
Site Reliability Engineer
Ardent SoftSol Inc.
Calgary, AB
- Contract
This is an active and ongoing hiring requirement for a SRE Engineer, We are specifically looking for Developers or Core SRE Application Support professionals. This position is based in…
Added 4 hours ago
SD
Full Stack AI Engineer
Symbiotic Digital
ON · Downtown Toronto (Central Bay Street), Ontario
- Contract
We are seeking a Full Stack AI Engineer with demonstrated
Added 4 hours ago
Y
SRE Engineer
Yochana
Calgary, AB
- Full-time
The Wealth Management Production Management Site Reliability Engineer position is a highly visible/critical role, which will be a team member of technical SMEs managing the stability and…
Added 5 hours ago
MP
Lead Data Engineer
Municipal Property Assessment Corporation
Pickering, ON
- Full-time
Hands-on experience with enterprise cloud data engineering technologies and programming languages such as SQL, Python, Java, Groovy, Spring Boot, Spark, Microsoft Fabric, Databricks, Azure…

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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