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Added 3 hours ago
SB
Senior Hydraulics and Capacity Engineer
South Bow
Calgary, AB
- Full-time
We are seeking a Senior Hydraulics and Capacity Engineer to provide technical leadership and strategic oversight of operational capacity management for South Bow's crude oil pipeline…
Added 6 hours ago
M-
Développeur Logiciel Principal.e, Plan de Contrôle - Laboratoire d'IA Souveraine
Mila - Institut québécois d'intelligence artificielle
Montreal, QC
- Full-time
…together functionalities such as model serving, retrieval, agent orchestration, observability, and a control plane to operate these components as one coherent…
Added 7 hours ago
M-
Spécialiste en intégration de systèmes, IA souveraine
Mila - Institut québécois d'intelligence artificielle
Montreal, QC
- Full-time
…infrastructure they control. It combines model serving, retrieval, agent orchestration, and observability, with a control plane to operate them as one…
Added 9 hours ago
NS
Senior Applied AI Engineer
Network Solutions
Canada
- Full-time
We are looking for a hands on Senior Applied AI Engineer who combines strong software engineering with practical AI problem solving. You will build production AI experiences across Network…
Added 23 hours ago
BJ
Law Clerk, Intellectual Property/Litigation
Bennett Jones
Toronto, ON
- Full-time
Review, audit, and systematically process vendor, agent, and expert witness invoices related to active litigation
Added 1 day ago
TW
Senior Support Engineer
Town Web
Remote, Canada
- Full-time
- Remote
This is the senior seat on our Client Success team. We are hiring you to raise the standard of our support: fix what is broken, write down how it should work, and show what great looks like.
Added 3 days ago
Customer Service Representative Level 2
Transx Ltd
Rosser, MB
…Representative proactively contacts customers with service updates, recovery plans, and corrective actions taken to improve customer…
Added 3 days ago
MG
Director, Legal & Loan Operations
MarshallZehr Group Inc.
Waterloo, ON
- $110,000 to $130,000 CAD / year
- Full-time
Reporting to the Senior Vice President, Risk, Legal & Finance (the “SVP”), the Director, Legal & Loan Operations (the “Director”) will lead MarshallZehr’s legal and loan operations function…
Added 4 days ago
DI
MLOps Engineer – Databricks (1896) $90-100hr
Direct IT Recruiting Inc.
Toronto, ON
- $90 to $100 CAD / hour
- Contract
Develop operational runbooks, support procedures, incident response guidance, and recovery processes.
Added 4 days ago
E
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
Evinova
Mississauga, ON
- Full-time
As a Senior Cloud Platform Engineer on the ML/AI Ops team, you will design, build and operate the AWS platform that runs our production Generative AI, agentic AI and conversational AI…
Added 4 days ago
Senior Agentic AI Engineer- Physical AI hub, Kitchener
Siemens
Kitchener, ON
We are seeking a Senior Agentic AI Engineer to build the harness reasoning, monitoring, recovery, and completion-gating capabilities for the Physical AI Runtime. This engineer will design…
Added 5 days ago
A
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
AstraZeneca
Mississauga, ON · Canada - Mississauga
- Full-time
As a Senior Cloud Platform Engineer on the ML/AI Ops team, you will design, build and operate the AWS platform that runs our production Generative AI, agentic AI and conversational AI…
Added 5 days ago
S
Senior Agentic AI Engineer- Physical AI hub, Kitchener
Siemens
Kitchener, ON
- Full-time
We are seeking a Senior Agentic AI Engineer to build the harness reasoning, monitoring, recovery, and completion-gating capabilities for the Physical AI Runtime. This engineer will design…
Added 5 days ago
GM
Senior Chassis Diagnostic Engineer – Driveline & Trailering
General Motors
Markham, ON
- Full-time
…strategies, DTC implementation requirements, fault maturation and recovery criteria, and diagnostic validation plans for production vehicle pro Experience defining diagnostic requirements,…
Added 8 days ago
M
Senior Platform Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
As a Senior Platform Engineer, you will build and operate the shared platform that application teams use to deploy and run services on Azure Kubernetes Service. You will work with…
Added 10 days ago
NR
Senior Data Platform Engineer
Norton Rose Fulbright
Toronto, ON · Calgary, AB
- Full-time
The Senior Data Platform Engineer will act as a technical lead for our technologies in any project or initiative, and is responsible for designing, developing, implementing, and supporting…
Added 11 days ago
N(
Technical Systems Analyst, Student Systems
NAIT (Northern Alberta Institute of Technology)
AB · Edmonton, AB
- Full-time
This is a senior-level role involving highly complex, non-routine technical problems. You will work both independently and as part of a team, collaborate with internal clients, vendors and…
Added 11 days ago
B
Director, Wealth Digital AI Platforms & Technology Delivery
BMO
Toronto, ON · BMOPLACE
- Full-time
This is a senior delivery leadership role requiring the coordination of cross-functional teams across Engineering, Architecture, Security, Risk Management, Compliance, and Business…
Added 12 days ago
T
Senior Data Platform Engineer - Toronto
Trisura
Toronto, ON
- Full-time
We are currently seeking a driven and collaborative Senior Data Platform Engineer to join our forward-thinking Data and Analytics team.
Added 12 days ago
KL
AI Solutions Architect
KLONDIKE Lubricants Corporation
Langley (District), BC · Langley, BC
- Full-time
…opportunities into working AI-enabled solutions. This is a senior individual-contributor role for someone who can bridge business process, software integration, automation, applied AI, and…
Added 12 days ago
Senior Data Platform Engineer - Toronto
Trisura Guarantee Insurance Company
Toronto, ON
We are currently seeking a driven and collaborative Senior Data Platform Engineer to join our forward-thinking Data and Analytics team.
Added 12 days ago
UR
Senior Agentic Engineer - JavaScript
Urban Ridge Supplies
Toronto, ON
- Full-time
Build and refine agent loops that support planning, tool selection, execution, observation, reflection, recovery, and termination.
Added 12 days ago
UR
AI Platform Engineering Lead
Urban Ridge Supplies
Toronto, ON
- Full-time
…workloads to governed enterprise data, ensuring every deployed agent and model is identified, permissioned, monitored, and auditable. Platform scope include but are not limited to…
Added 12 days ago
UR
Senior Agentic Engineer - JavaScript
Urban Ridge Supplies
Toronto, ON
- Full-time
Build and refine agent loops that support planning, tool selection, execution, observation, reflection, recovery, and termination.
Added 12 days ago
P
Performance & Restructuring Manager
PwC
Toronto, ON
- Full-time
In deal recovery management at PwC, you will focus on helping clients navigate financial distress and recover from challenging business situations. You will be responsible for providing…

Closed listing

Dawn InfoTek

Senior Applied Intelligence Platform Engineer

Toronto, ON, Canada

Contract

This opening has closed.

The original listing is kept below for reference.

Find open jobs More jobs with this employer

About employer

Job details

Job type: Contract
Closing date: Nov 4, 2026
Posting language: English
Posted: Oct 5, 2026

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Original job description

Archived listing. The details below describe a past opening.

Dawn InfoTek Inc. is a professional IT consulting firm that partners with major financial institutions, investment firms, and government organizations. We are committed to delivering cutting-edge IT consulting services and providing highly qualified talent for a wide range of technology positions.

We are currently seeking a Senior Applied Intelligence Platform Engineer to join our dynamic team and work with one of client.

Title: Senior Applied Intelligence Platform Engineer

Contract Duration: ASAP to December 24, 2027

Overview

Applied Intelligence is scaling enterprise AI across Microsoft Foundry, Databricks, Copilot Studio, and a mixed model estate spanning Anthropic, Azure OpenAI, other frontier models, and open source models.

This hands-on engineering role partners with AI Governance and Risk to translate NIST AI RMF and enterprise requirements into practical platform controls, reusable patterns, automated guardrails, and governance evidence across the AI lifecycle.

Who you'll work with:

You'll join the Applied Intelligence Platforms team and work closely with Platform Engineering, Data Engineering, Enterprise Architecture, Privacy, Enterprise Security, AI Governance and Risk, and the AI Centre of Excellence. You will report to the Senior Manager, Applied Intelligence Platforms.

What you'll do:

Apply safe deployment practices including automated builds, artifact versioning, deployment gates, and rollback strategies such as blue/green, canary, and shadow, avoiding manual production changes.
Develop operational runbooks, support procedures, incident response guidance, and recovery processes.

Responsible AI, Privacy and Governance Enablement

Partner with AI Governance, Privacy, Information Security, and the AI Centre of Excellence to translate enterprise requirements into practical implementation patterns.
Implement technical guardrails supporting responsible AI outcomes, including content safety, grounding, human-in-the-loop checkpoints, and auditability.
Apply secure AI implementation patterns aligned with OWASP guidance for LLM and agentic systems, mitigating risks such as prompt injection, insecure tool usage, model exfiltration, and data leakage.
Implement authentication and authorization flows using OAuth2 and OIDC so AI agents and services inherit appropriate user context and role-based access.
Implement privacy-supporting controls in AI solutions, such as data minimization, access scoping, retention alignment, and handling of sensitive data in prompts, logs, and retrieval sources.

AI delivery model

Define and operationalize the AI delivery model, including reusable implementation patterns, reference solutions, and engineering standards for RAG, agentic, and machine learning solutions.
Select and integrate models across the estate based on suitability, performance, and cost.
Partner with delivery teams to accelerate build and support production readiness.

MLOps, LLMOps and evaluation

Build and maintain pipelines covering development, evaluation, deployment, monitoring, and model lifecycle management.
Establish evaluation frameworks with measurable quality criteria, behavioural regression testing, and continuous evaluation of probabilistic systems.
Implement lineage, experiment tracking, and reproducibility using tools such as MLflow.

AI governance technical implementation

Translate NIST AI RMF and enterprise AI governance requirements into technical controls across Govern, Map, Measure, and Manage.
Implement reusable guardrails through platform configuration, CI/CD/IaC, evaluation gates, access controls, policy enforcement, and OWASP-aligned secure AI patterns.
Establish traceable governance evidence for models, agents, deployments, evaluations, approvals, and human-in-the-loop controls.
Partner with AI Governance and Risk to validate control effectiveness and escalate policy, privacy, security, and risk-acceptance decisions to accountable teams.

Operations, reliability and cost

Own the reliability, observability, and production support of enterprise AI services.
Own cost tracking, attribution, and optimization, treating cost as a measurable engineering metric.
Apply safe deployment practices and maintain runbooks, incident response, and recovery processes.
Enablement
Onboard teams onto approved AI platforms and patterns, and provide technical mentorship, documentation, and reusable assets.

Decision making

Independent analysis approach based on business context

What you'll need:

Qualifications:

Has shipped and supported production systems, and designs for failure.
Has debugged performance or latency issues in distributed systems.
Writes modular, testable code and favours automation over manual intervention.
Defines measurable success criteria before building, and can test systems where outputs vary.
Treats cost as a measurable engineering metric.
Bachelor's degree in a related technical field, or equivalent practical experience.

Knowledge:

Generative AI, LLMs, RAG, agentic systems, and enterprise AI application patterns.
Microsoft Foundry, Databricks/Unity Catalog/MLflow, Copilot Studio, AI Gateway/model access patterns, and mixed-model tradeoffs.
MLOps/LLMOps, CI/CD, Infrastructure as Code, evaluation, observability, and cloud-native engineering.
NIST AI Risk Management Framework (Govern, Map, Measure, Manage) and translation into engineering controls.
Responsible AI, human-in-the-loop design, auditability, privacy, IP, security, bias, and model misuse risks.
Cloud fundamentals, distributed systems and API design, observability, and data literacy.
Cloud cost management, consumption tracking, and cost attribution.
Proficiency in Python.

Experience:

7+ years in software, AI, machine learning, platform, or cloud engineering.
Hands-on experience building and operating production AI or machine learning solutions.
Experience implementing RAG and agent-based solutions.
Experience implementing MLOps and LLMOps capabilities end to end.
Experience implementing automated AI governance controls or evidence, ideally mapped to NIST AI RMF or another recognized framework.
Experience owning cost tracking and optimization of cloud or AI workloads.
Experience in a regulated environment is an asset.
Experience collaborating with Enterprise Architecture, Platform Engineering, Privacy, Security, and Governance teams in a large organization.
Experience in financial services, pension, asset management, or another regulated environment is an asset.

About employer

More about this job

Responsibilities

Build and operate production AI platforms and solutions, including reusable patterns, model evaluation and lifecycle pipelines, secure deployment controls, and reliable, observable services. Translate AI governance, privacy, and security requirements into automated guardrails and traceable evidence, while managing costs and enabling delivery teams.

Requirements

Requires a bachelor's degree in a related technical field or equivalent practical experience, at least seven years of relevant engineering experience, and hands-on experience building and operating production AI or machine learning solutions. Candidates should be proficient in Python and experienced with RAG, agent-based systems, MLOps/LLMOps, cloud engineering, AI governance controls, and cost optimization.

Skills

Python
Generative AI
Large Language Models
Retrieval-Augmented Generation
Agentic Systems
MLOps
LLMOps
Microsoft Foundry
Databricks
MLflow
CI/CD
Infrastructure as Code
NIST AI Risk Management Framework
OAuth2
OpenID Connect
Cloud Cost Management

Visa sponsorship

Not detected in the job text

Keywords

Applied Intelligence
Generative AI
Large Language Models
Retrieval-Augmented Generation
Agentic Systems
Machine Learning
Microsoft Foundry
Databricks
Unity Catalog
Copilot Studio
Anthropic
Azure OpenAI
Python
MLOps
LLMOps
MLflow
CI/CD
Infrastructure as Code
NIST AI Risk Management Framework
Responsible AI
Human-in-the-Loop
OAuth2
OpenID Connect
OWASP
Model Evaluation
Observability
Cloud Cost Management
Distributed Systems
AI Governance
Financial Services

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