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Added 15 mins ago
RB
Staff AI Architect/Engineer
Royal Bank of Canada
Toronto, ON
- Full-time
This is a tremendous opportunity to reinvent architecture in the AI Age. As a Staff AI Architect/Engineer, you will operate at the intersection of hands-on AI building and enterprise…
Added 15 mins ago
Z
Senior Software Developer
Zynga
Toronto, ON
- $99,800 to $147,680 CAD / year
…job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also…
Added 15 mins ago
Staff Information Security Engineer - Threat Detection & Response
Visier Solutions Inc
Vancouver, BC
Founded in 2010 by the pioneers of business intelligence, we have over 85,000 customers in 75 countries - including enterprises like BASF, Panasonic, Domino’s Pizza, Experian, Amgen, eBay,…
Added 30 mins ago
ML
IT Security Consultant
Maple Leaf Foods Inc
Mississauga, ON
- $96,000 to $141,000 CAD / year
- Full-time
Leading and participating in Network vulnerability evaluations and assessments, Digital forensics, Threat intelligence analysis Active cyber tasks, Malware identification and analysis
Added 30 mins ago
E
Environmental Scientist Project Manger
Englobe
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- Full-time
Build and maintain strong relationships with clients, regulators, contractors, and internal stakeholders while supporting business development opportunities;
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EM
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Langley (District), BC · Langley, BC
- Full-time
…helping those teams adopt the change. You are not a software engineer and you will not manage people. You are the person who can walk into an office, understand how the work actually gets…
Added 45 mins ago
C
Senior Java Engineering Lead
Citi
Mississauga, ON
- Full-time
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the…
Added 1 hour ago
Senior Software Engineer, Security Engineering - Platform (Auth0)
Okta
Toronto, ON
Senior Software Engineer, Security Engineering
Added 1 hour ago
Business Intelligence Engineer, Forecasting & Labs Analytics
Amazon
Toronto, ON
We need a creative, smart and enthusiastic Business Intelligence Engineer. Your mission will be to improve forecast accuracy and enable partner teams and customers to optimize supply chain…
Added 1 hour ago
DI
Senior Applied Intelligence Platform Engineer
Dawn InfoTek
Toronto, ON
- Contract
We are currently seeking a Senior Applied Intelligence Platform Engineer to join our dynamic team and work with one of client.
Added 1 hour ago
T|
Director, Digital Platforms & Architecture
TALTEK | TALENT in TECHNOLOGY
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Intelligence artificielle et technologies émergentes
Added 2 hours ago
M
Associate Applied AI Engineer – GenAI Systems
Manulife
Toronto, ON
- Full-time
…that move from idea to implementation and are adopted in real business…
Added 2 hours ago
AI Engineer
Bell
Toronto, ON
…systems, delivering autonomous agentic workflows, conversational intelligence, and machine learning systems that transform our internal operations and customer…
Added 2 hours ago
H
Senior BI Engineer
Hays
Toronto, ON
- $80 to $95 CAD / hour
- Contract
5+ years of experience in Business Intelligence, Reporting, or BI Development
Added 2 hours ago
CS
Specialist, Reliability
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Windsor, ON
- Full-time
…friends every day, and realizing our potential as people and as a…
Added 2 hours ago
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AI Development & Continuous Improvement Student (Summer 2027)
J.D. Irving, Limited
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 2 hours ago
OD
Data Engineer / BI Developer – GCP, dbt & Power BI
OSI Digital
Vancouver, BC
- $40,000 to $90,000 CAD / year
- Full-time
2–4 years of experience in Data Engineering, Business Intelligence, or Analytics Engineering.
Added 2 hours ago
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Data Engineer / BI Developer – GCP, dbt & Power BI
OSI Digital
Toronto, ON
- $40,000 to $90,000 CAD / year
- Full-time
2–4 years of experience in Data Engineering, Business Intelligence, or Analytics Engineering.
Added 2 hours ago
C
Lead Java Developer, Vice President
Citi
Mississauga, ON
- Full-time
Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations,…
Added 2 hours ago
BS
QA Automation Engineer – Power BI / Digital Banking
BULL-IT SOLUTIONS LTD
Toronto, ON
- Full-time
…accuracy, and reliability of both digital banking applications and business intelligence reporting solutions within the Digital Banking Platform.Top 3 Required Skills :- PowerBI, Java,…
Added 3 hours ago
XI
Analytics Engineer, Network Intelligence
Xplore Inc.
Canada
- Full-time
…AI/BI dashboards that surface real-time and historical network intelligence across Fiber, Fixed Wireless, and Satellite domains. This role is not limited to cloud migration work: it also…
Added 3 hours ago
RV
Radical Ventures: AI Product Engineer
Radical Ventures
Toronto, ON
- Full-time
we partner with the world’s most transformative founders in artificial intelligence. Learn more
Added 3 hours ago
X
Engineer
Xero
Vancouver, BC
- Full-time
You will deliver high-quality, impactful software that aligns with team and business goals, always keeping customer needs and outcomes front of mind. By identifying and solving complex,…
Added 3 hours ago
S
Technical Presales
Survalent
Mississauga, ON
- Full-time
…motivated individual to join our Sales team. The Pre-Sales Engineer will play a key role in partnering with Sales to identify the right technology solutions for both prospects and existing…
Added 3 hours ago
S
Technical Presales
Survalent
Toronto, ON · Greater Toronto Area, Canada
- Full-time
…motivated individual to join our Sales team. The Pre-Sales Engineer will play a key role in partnering with Sales to identify the right technology solutions for both prospects and existing…

Dawn InfoTek

Senior Applied Intelligence Platform Engineer

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 4, 2026
Posting language: English
Posted: Oct 5, 2026

Original job description

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.

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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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