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About the Role

This Enterprise AI Engineer role is foundational to establishing Porter's enterprise AI capability. You will design, build, test, and operationalize AI-enabled solutions to address business problems and create value across the organization. The role focuses on applied AI engineering, owning the AI solution lifecycle from concept to operational use, including establishing engineering standards, evaluation methods, deployment practices, and monitoring.

Responsibilities

Design, develop, test, and deploy AI-enabled applications, tools, workflows, and prototypes.
Develop practical AI solutions using machine learning, generative AI, agentic AI, and custom software engineering.
Support the design, development, evaluation, fine-tuning, and deployment of machine learning models.
Develop robust Python-based applications, scripts, services, APIs, and data pipelines.
Translate ambiguous business problems into technical solutions, working with stakeholders to identify requirements and constraints.
Work with structured and unstructured data from enterprise systems and other sources.
Lead the development of reusable AI engineering patterns, coding standards, and evaluation approaches.
Evaluate AI tools, platforms, libraries, and vendors.
Help define technical architecture and implementation standards for Porter’s AI ecosystem.
Identify technical risks, limitations, and security concerns related to AI solutions.
Prepare technical documentation and knowledge-sharing materials.
Provide technical leadership and guidance to business teams and stakeholders.
Remain current on emerging AI technologies and development practices.
Operate with a high degree of ownership in a new and evolving AI practice.
Actively participate in Porter’s Safety Management System (SMS).

Requirements

Post-secondary education in a related technical discipline or equivalent practical experience.
Strong hands-on software development experience with advanced proficiency in Python.
Experience developing, deploying, and integrating machine learning models.
Practical experience with generative AI, large language models, retrieval-augmented generation, semantic search, or LLM-based application development.
Experience building APIs, services, scripts, automation workflows, data pipelines, or backend processes.
Strong understanding of software engineering best practices.
Experience working with structured and unstructured data.
Experience with AI frameworks, orchestration tools, or libraries.
Understanding of data privacy, cybersecurity, responsible AI, model risk, governance, and enterprise control requirements.
Strong analytical and problem-solving skills.
Demonstrated ability to learn new technologies quickly and independently.
Ability to balance experimentation and delivery.
Strong communication skills.
Ability to work independently with minimal structure.
Experience in a regulated, operationally complex, customer-facing, transportation, airline, financial services, or similar environment is considered an asset.
Experience with agentic AI patterns, tool-calling, workflow orchestration, autonomous or semi-autonomous processes, and human-in-the-loop controls is considered an asset.

Skills

Python
Machine Learning
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Semantic Search
LLM-based application development
API development
Service development
Scripting
Automation workflows
Data pipelines
Software engineering best practices
Version control
Testing
Modular design
Documentation
Code review
Error handling
Maintainability
Structured data
Unstructured data
SQL databases
Files
APIs
Documents
Logs
Enterprise data sources
AI frameworks
Orchestration tools
PyTorch
TensorFlow
scikit-learn
LangChain
LlamaIndex
Hugging Face
FastAPI
Agentic AI patterns
Tool-calling
Workflow orchestration
Autonomous processes
Semi-autonomous processes
Human-in-the-loop controls
Data privacy
Cybersecurity
Responsible AI
Model risk
Governance
Enterprise controls
Analytical skills
Problem-solving skills
Communication skills

Location

Toronto Downtown Office (250 Yonge Street)

Work Type

Hybrid

Experience Level

Foundational role
Applied AI engineering
Broad responsibility
High degree of ownership
Adaptability
Curiosity
Problem-solving capability
Comfortable working in a new and evolving function
Strong technical builder

Education Level

Post-secondary education in Computer Science, Data Science, Machine Learning, Engineering, Mathematics, Statistics, or a related technical discipline
Equivalent practical experience

About the Company

Since 2006, Porter Airlines has been elevating the experience of economy air travel for every passenger, providing genuine hospitality with style, care and charm.
Porter’s fleet of Embraer E195-E2 and De Havilland Dash 8-400 aircraft serves North America, including a coast-to-coast domestic Canadian network, the U.S., Mexico, the Caribbean and Central America.
Headquartered in Toronto, Porter is an Official 4 Star Airline® in the World Airline Star Rating®.