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Intermediate IT AI Architect
LinkedIn Recruiter Post
Intermediate IT AI Architect to develop AI strategies and architecture models. Bridge high - level strategy with technical execution in a hybrid Toronto role.
About the role
- AI Developer designs & deploys AI solutions using LLMs & predictive models. Builds data pipelines in Azure/Databricks for intelligent search, conversational apps & decision support.
Responsibilities
- The Artificial Intelligence Developer designs, develops, deploys, and maintains advanced artificial intelligence solutions supporting enterprise business objectives. The role builds production ready systems using large language models, predictive models, and document intelligence for intelligent search, conversational applications, document understanding, and decision support. Responsibilities include working with business partners to understand operational needs and translating those into technical solutions. The role develops data pipelines processing structured and unstructured data such as documents, spreadsheets, images, and text. The Artificial Intelligence Developer ensures data quality, traceability, and compliance with organizational policies. The role covers the full lifecycle of artificial intelligence solutions including model development, integration, deployment, monitoring, and maintenance. Work is performed primarily within Microsoft Azure and analytics platforms such as Databricks. The Artificial Intelligence Developer designs agent based artificial intelligence systems capable of planning, reasoning, and executing multi-step objectives. Modern software development practices including GitHub, peer code review, and structured change management are required.
Requirements
- Qualifications - Bachelor’s degree in computer science, engineering, data science, mathematics, physics, or related discipline. - Advanced degree is considered an asset. Skills and Experience - Strong programming skills using Python. - Experience designing artificial intelligence systems using large language models and predictive modeling. - Experience building data pipelines for structured and unstructured data. - Experience deploying artificial intelligence solutions in cloud environments, Azure preferred. - Experience using Databricks for data preparation and scalable processing. - Experience applying machine learning operations including versioning, deployment, monitoring, and lifecycle management. - Proficiency with GitHub for source code management and peer review. - Strong understanding of software engineering best practices. - Ability to communicate complex technical concepts clearly. - Experience delivering artificial intelligence solutions from concept to production. - Professional certifications related to cloud computing, data platforms, or artificial intelligence technologies are considered an asset.
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