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Senior Security Engineer, AWS Foundational Services Security
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Vancouver, BC
We're looking for a Security Engineer to join the team that secures the foundational Identity and crypto systems powering AWS.

BlackBerry

AI Engineering Specialist

Toronto, ON, Canada
Waterloo, ON, Canada

$108,750.00 - $152,250.00 · Full-time

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Job details

Pay: $108,750.00 - $152,250.00
Job type: Full-time
Apply by: Nov 16, 2026
Posting language: English
Posted: Oct 29, 2026

Original job description

Worker Sub-Type:

Regular

Job Description:

About the role

BlackBerry IT is investing in practical, secure AI to make every employee more capable. We're hiring an AI Engineering Specialist to sit at the intersection of the business and our AI platform. The person teams come to when they want to understand what's possible, and the person who then builds it, and deploys it to the cloud

This is a a builder-enabler role: you'll embed with functions across BlackBerry (Finance, Sales, Legal, HR, Operations, Engineering support), find the highest-value use cases, prototype agents and copilots, deploy them securely across our Azure and AWS environments, and turn one-off wins into reusable patterns that scale. Throughout, you'll keep less-technical colleagues firmly in the driver's seat.

What you'll do

Find and frame the value

Embed with business teams to map their processes and pain points and identify where AI agents create the highest leverage.
Translate ambiguous business problems into well-scoped AI solutions with clear before/after metrics.

Build and deploy

Rapidly prototype and ship AI solutions using Python and LLM APIs (e.g., Azure OpenAI, Amazon Bedrock, Anthropic Claude).
Build agents and copilots using Microsoft Copilot Studio, Azure AI Foundry, and the M365 ecosystem; extend Copilot with custom plugins and declarative agents that surface enterprise data in Teams and Office.
Build and orchestrate agents on AWS using Amazon Bedrock (Agents, Knowledge Bases, Guardrails) and related services.
Deploy and operate agents on cloud infrastructure leveraging Azure (Container Apps, Functions) and AWS (Lambda, ECS/Fargate, Bedrock), with appropriate state management, monitoring, and cost controls.
Implement RAG patterns over BlackBerry's enterprise content using Azure AI Search and/or Amazon Bedrock Knowledge Bases / OpenSearch (vector + semantic search).

Enable less-technical users

Turn skeptics into users and users into builders.
Create self-serve templates, playbooks, and guardrailed building blocks so business users can safely create and run their own agents.
Act as the bridge between the platform/engineering teams who build foundational capability and the business who consumes it, translating requirements in both directions.

Do it securely and responsibly

Partner with Security, Privacy, and Governance to ensure every deployment meets BlackBerry's data-protection, access-control, and Responsible AI standards - fitting for a company whose business is trust and security.
Apply cloud-native security controls across providers (Azure managed identities/private endpoints/content safety; AWS IAM, VPC endpoints, Bedrock Guardrails).
Build evaluation, human-in-the-loop, and monitoring practices in from day one.

What you'll bring

Required

4+ years in software/AI/data engineering or technical consulting, with hands-on delivery of working solutions (not just prototypes).
Strong Python; experience integrating LLM APIs and building agentic or RAG workflows.
Experience deploying applications to Azure and/or AWS, including containerized/serverless patterns.
Proven ability to explain complex technical topics to non-technical audiences and to context-switch between a deeply technical and a commercial conversation.

Preferred

Hands-on with the AWS AI stack: Amazon Bedrock, SageMaker, Lambda, and AWS agent/orchestration tooling.
Hands-on with the Microsoft GenAI stack: Copilot Studio, Azure AI Foundry, M365 Copilot extensibility, Power Platform.
Familiarity with agent frameworks/orchestration and agent protocols such as MCP.
Cloud certifications such as AWS Certified Machine Learning / AI Practitioner or Microsoft Azure AI Engineer Associate.
Experience embedding Responsible AI, evaluation frameworks, and enterprise security controls.
Background working in a security or compliance-sensitive enterprise.

Scheduled Weekly Hours:

Compensation Hiring Base Salary Range:

$108,750.00 - $152,250.00

Please be advised that the compensation hiring range indicated herein is provided solely as a good-faith estimate of expected base compensation for the position. The actual compensation offered will be determined at the time of hire and is contingent upon multiple factors, including but not limited to the candidate’s qualifications, relevant experience, demonstrated skills, and results of assessments conducted during the hiring process.

Bonus:

The BlackBerry Variable Incentive Pay (VIP) program is an organization-wide bonus incentive program which aims to reward full-time eligible employees for their contribution to BlackBerry’s success. VIP payments are made in addition to base salary and factor in company’s performance as a way for employees to share in BlackBerry’s achievements.

Benefits:

The BlackBerry Employee Benefits programs offer a wide range of benefits that support your physical, financial and personal well-being. BlackBerry remains committed to offering affordable benefits including coverage for medical, dental, vision, life, disability insurance, retirement, employee share purchase program and paid-time-off to those that meet the eligibility requirements.

Disclosure of Position Status:

This is an active opening. We are seeking to fill this position immediately

Disclosure of Artificial Intelligence:

We do not use artificial intelligence (AI) to screen, assess, or select applicants at any stage of our recruitment process. All applications are reviewed and evaluated by our hiring team.

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More about this job

Responsibilities

The AI Engineering Specialist will embed with various business teams to identify high-value use cases and prototype AI agents and copilots. They will deploy these solutions securely across cloud environments while enabling non-technical users to build and manage their own AI tools.

Requirements

Candidates must have 4+ years of experience in software, AI, or data engineering with strong proficiency in Python and LLM integration. Experience deploying applications to Azure or AWS and the ability to communicate complex technical concepts to non-technical stakeholders are required.

Skills

Python
LLM APIs
Azure OpenAI
Amazon Bedrock
Microsoft Copilot Studio
Azure AI Foundry
RAG patterns
Cloud infrastructure
Containerization
Serverless patterns
Data engineering
Technical consulting
Agentic workflows
Security controls
Responsible AI
System architecture

Benefits

Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
Retirement plan
Employee share purchase program
Paid time off

Visa sponsorship

Not detected in the job text

Keywords

AI Engineering
Python
LLM
Azure
AWS
Amazon Bedrock
Microsoft Copilot Studio
RAG
Cloud-native
Container Apps
Lambda
ECS
Fargate
Vector search
Semantic search
Responsible AI
Data protection
IAM
VPC
Software engineering
Data engineering
Technical consulting
Agentic workflows
Orchestration
Compliance
Security
Automation
Enterprise data
API integration
Machine learning

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