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Added 14 mins ago
T
Software Engineer I - Development and Quality Engineering
TD
Toronto, ON
- Full-time
The Risk Technology team within the Finance and Risk Platform group is a dynamic, high-performing, and fast-paced team supporting enterprise credit risk applications used for the Bank’s…
Added 16 mins ago
SI
Cloud Engineer
Spait Infotech
Canada
- Full-time
Strong hands-on experience with at least one major cloud platform:
Added 16 mins ago
TC
Data Engineer
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
Strong banking and financial services domain experience with demonstrated expertise in data warehouse and cloud data platform implementations.
Added 16 mins ago
QW
Observability Engineer
Quantum World Technologies Inc.
Montreal, QC
- Contract
We are looking for an experienced Observability Engineer to design, implement, and maintain enterprise observability solutions across cloud, application, infrastructure, and distributed…
Added 16 mins ago
QT
Site Reliability Engineer
Q1 Technologies, Inc.
Toronto, ON
- $95,000 to $115,000 CAD / year
- Full-time
As an Intermediate Site Reliability Engineer, you will support and continuously improve enterprise Azure and Databricks platforms. The role focuses on production reliability, monitoring,…
Added 16 mins ago
AI
Oracle EDQ Platform Engineer
Aptino, Inc.
Brampton, ON
- Contract
We are looking for an experienced Oracle EDQ Platform Engineer to support the migration of Oracle Enterprise Data Quality (EDQ) from on-premises environments to Microsoft Azure Cloud.
Added 16 mins ago
IS
Senior Data Engineer
Iris Software Inc.
Mississauga, ON
- Contract
Iris's Direct client, a highly diversified financial services provider based in Canada is looking to hire a Sr. Data Engineer for a Long Term Contract opportunity.
Added 16 mins ago
H
Senior Python Engineer - Data Platforms
Highspring
Montreal, QC
- Full-time
Highspring est à la recherche d'un(e) Senior Python Engineer pour rejoindre une équipe de haut niveau spécialisée en Data & IA. Ce rôle s'adresse à un développeur logiciel passionné par…
Added 28 mins ago
LC
Site Reliability Engineering I
Loblaw Companies Limited
Brampton, ON
- Full-time
The Site Reliability Engineer I will run the production environment by monitoring availability and taking a holistic view of system health. You will build tools and systems to manage…
Added 48 mins ago
ZS
Monitoring Tool Automation Engineer
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Job Title: Monitoring Tool Automation Engineer
Added 48 mins ago
V
Data Engineer
VySystems
Halifax, NS
- Contract
Design and implement complex ETL/ELT workflows for diverse data sources both on-prem and Cloud platform (AWS)
Added 48 mins ago
ZS
DevOps Engineer or Platform Engineer with AI - FTE
Zodiac Solutions, Inc
Halifax, NS
- Full-time
Role: DevOps Engineer or Platform Engineer with AI
Added 48 mins ago
IS
Data Engineer Tech Lead
Iris Software Inc.
Mississauga, ON
- Contract
Must have skills5-8 years SQL & Python; cloud data platform experience (Snowflake highly preferred)
Added 48 mins ago
Senior SailPoint Support Engineer
KeyData Cyber
Toronto, ON
We are currently looking to hire a Senior SailPoint IIQ Support Engineer to join KeyData Cyber's Managed Services team who will step in and own our largest and most important customer…
Added 1 hour ago
Data Engineer - Analytics
Capgemini
Montreal, QC
Engineer observability solutions that proactively monitor configuration changes, control performance, operational trends, risk signals, and testing outcomes.
Added 1 hour ago
HR
AI Forward Deployed Engineer - CRM & Marketing
Hard Rock Digital
Remote, Canada
- Full-time
- Remote
We're hiring an AI Forward Deployed Engineer to build agentic and generative AI for CRM and Marketing. You'll ship production features, not prototypes, that help us acquire, engage, and…
Added 1 hour ago
M
Spécialiste infonuagique et DevOps / Cloud & DevOps Specialist
Montrium
Montreal, QC
- Full-time
Added 1 hour ago
AT
Senior Data Engineer
Arkhya Tech Inc.
Ottawa, ON
- Contract
This position is for a Senior Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems
Added 1 hour ago
VC
Python Developer
VBeyond Corporation
Toronto, ON
- Full-time
Backend Engineer – Python (API & Platform Engineering)
Added 1 hour ago
Applied AI Engineer
ContactMonkey
Toronto, ON
This is an AI engineering role with real infrastructure ownership. You won't be handed a platform - you'll help build the one our AI features run on. If you like being close to both the…
Added 1 hour ago
T
Software Engineer I
TD
Toronto, ON
- Full-time
The Risk Technology team within the Finance and Risk Platform group supports non-external-facing credit risk applications used for the Bank’s regulatory capital calculations and reporting…
Added 1 hour ago
S
Senior Data Engineer
Scene+
Toronto, ON
- Full-time
Reporting to the Senior Manager, Data Engineering and Data Governance, we are looking for a Senior Data Engineer who will play a pivotal role in shaping the next generation of Scene+’s data…
Added 1 hour ago
IC
Forward Deployed AI Engineer – System Test Automation
Infomatics Corp
Ottawa, ON
- Contract
We are seeking a Forward Deployed AI Engineer (FDE) to accelerate the real-world adoption of AI within our End-to-End System Test Automation. This role focuses on taking AI tools and…
Added 2 hours ago
DC
Electrical Engineer
Dillon Consulting Limited
Halifax, NS
- Full-time
We are currently seeking an Electrical Engineer to join our Halifax team. As our pipeline of new and ongoing projects continues to expand, you will have the opportunity to make an immediate…
Added 2 hours ago
AW
Cloud Architect
Agilus Work Solutions
Toronto, ON
- $60 to $80 CAD / hour
- Contract
We are looking for a Senior Business Intelligence Engineer to support the development of a Consolidated Ad Revenue Reporting platform. This role sits at the intersection of Data…

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.

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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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