AI Engineering Specialist

BlackBerry•Waterloo, ON

1d•CA$108,750 - CA$152,250

About The Position

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 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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.