Data Scientist Data & AI (Applied AI)

Air Canada•Toronto, ON

20h

About The Position

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation. As an Data Scientist (Agentic Engineer) within the Data Science & AI team at Air Canada, you will build, deploy, and operate production-grade agentic AI systems that deliver measurable business value. Working within an agentic squad, you will take designed agent workflows and transform them into scalable, reliable, and secure services across Air Canada's cloud environments (Azure and AWS). This role focuses on system engineering, deployment, CI/CD, and runtime performance, ensuring that agentic solutions operate reliably at enterprise scale. You will collaborate closely with Data Scientists, who own agent design, to deliver end-to-end production solutions. You will join the Data Science & AI Team, a central group within Air Canada's IT organization, supporting internal business units such as Revenue Management, Network Planning, Operations, Maintenance, Cargo, and customer-facing solutions. All initiatives follow an agile methodology, with 2-to-3-week sprints and incremental releases.

Requirements

5+ years of experience in software engineering, platform engineering, or ML engineering.
Strong hands-on experience with containerization (Docker) and Kubernetes.
Proven experience with cloud platforms, specifically Azure and AWS.
Strong experience designing and operating CI/CD pipelines.
Experience building and operating production API-based services.
Hands-on experience with observability tools (logging, tracing, monitoring).
Strong programming skills in Python and backend systems.
Experience with enterprise security, authentication, and integration constraints.
Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Nice To Haves

Familiarity with LLM-based systems and agentic architectures (LangGraph a plus).

Responsibilities

Package agentic AI solutions as containerized services with well-defined APIs.
Deploy and operate solutions across cloud platforms (Azure and AWS).
Design and maintain CI/CD pipelines for versioning, testing, and releasing agent services.
Manage runtime environments using Kubernetes and cloud-native services.
Integrate agentic solutions with enterprise data systems, APIs, and external services.
Implement and maintain monitoring, logging, tracing, and observability pipelines.
Ensure system performance across latency, scalability, reliability, and cost efficiency.
Enforce security, authentication, and access control (RBAC, identity integration).
Handle constraints from the existing enterprise stack (Azure, AWS, networking, security).
Collaborate with Data Scientists to ensure agent designs are production-ready.
Troubleshoot and resolve issues in deployed agent systems.
Contribute to platform standards and reusable runtime patterns for the agentic squad.