AI Developer & Integration Specialist

AI Developer & Integration Specialist

Date Posted: 02/24/2026

Req ID: 47033

Faculty/Division: Ofc of the Chief Information Officer

Department: Enterprise Infrastructure Solutions

Campus: St. George (Downtown Toronto)

Position Number: 00058956

Existing Vacancy: Yes

Description

About us

The Enterprise Infrastructure Solutions (EIS) group, part of the Information Technology Services (ITS) division, is responsible for campus core network, campus wireless, wide area network connectivity and internet connectivity for the University, including connectivity to research and education networks.

EIS is also responsible for services related to departmental network management, network, server and storage infrastructure, Windows and Linux server management services, database and application integration and support, enterprise backup service, 24/7 operation of central administrative data centres and telecommunications services.

If you’re motivated and passionate about learning technologies and dedicated to improving experiences for today’s student, consider a career with us.

Your Opportunity

Reporting to the Manager, AI Engineering & Operations within the Enterprise Infrastructure Solutions group, the AI Developer & Integration Specialist plays a critical role in developing, customizing and integrating AI applications, models and solutions into the University’s infrastructure and services. This role acts as a critical bridge between AI research and innovation and its practical, value-driven deployment, ensuring that all AI tools are usable, ethical and aligned with institutional goals.

Your Responsibilities Will Include

• Architecting and engineering complex, university-wide AI solutions, designing custom Retrieval-Augmented Generation (RAG) pipelines and autonomous agent workflows that meet strict institutional scalability and performance requirements.
• Designs and maintains robust MLOps and CI/CD pipelines (using GitHub Actions/GitLab), making authoritative decisions on the infrastructure code that governs model training, deployment, and versioning.
• Evaluates and selects appropriate foundational models (OpenSource vs. Proprietary) and hosting strategies (Azure AI Foundry, AWS Bedrock, local GPU/TPU), directly influencing the University's cloud spend and computational resource efficiency.
• Acts as the primary technical authority for AI security, implementing the OWASP Agentic AI framework to proactively identify and mitigate novel threats (e.g., prompt injection, insecure plugin design) before systems reach production.
• Establishes and enforces the Model Context Protocol (MCP) standards for theUniversity, ensuring a secure and standardized method for AI tools to access institutional data.
• Engineers complex authentication flows using OIDC, OAuth2, and SAML, ensuring that AI agents inherit correct user permissions and preventing unauthorized data exfiltration or privilege escalation.
• Conducts threat modeling for new AI integrations, serving as the 'gatekeeper' for approval on high-risk use cases involving sensitive or confidential data.
• Establishes the University’s observability standards for AI, implementing OpenTelemetry and tracing tools (e.g., Langfuse, MLFlow) to gain deep visibility into non-deterministic agent behavior and latency.
• Designs rigorous evaluation frameworks ("Evals") to systematically test models for accuracy, hallucination rates, and bias, creating the benchmarks against which all internal AI tools are measured.
• Solves unprecedented technical challenges related to stochastic software behavior, acting as the highest-level escalation point for complex debugging and performance optimization.

Essential Qualifications

• Bachelor’s degree in computer science, Software Engineering, Engineering, Data Science or acceptable combination of equivalent experience.
• Eight years or more years of experience in software development
• Three to five years of experience in software development with a specific focuson AI/ML, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Demonstrated experience in developing and integrating AI/ML models in an enterprise environment (e.g., RAG pipelines, vector databases, and secure function calling for AI agents).
• Experience developing and implementing the Model Context Protocol (MCP) to standardize context and tool exchange between AI models and data sources.
• Strong knowledge of authentication and authorization protocols, including OIDC (OpenID Connect), OAuth2, and SAML, specifically for securing AI agents, APIs, and user sessions.
• Experience implementing observability and OpenTelemetry standards for Agentic platforms to ensure deep visibility into agent behavior, latency, and performance.
• Proficiency with LLMOps, tracing, and evaluation tools such as Langfuse or MLFlow for managing model lifecycles and experiments.
• Familiarity with the OWASP frameworks and secure development best practices.
• Proficiency with CI/CD tooling for infrastructure delivery, such as GitHub, GitHub Actions, GitLab, or equivalent.
• Proven ability to evaluate, fine-tune, and optimize both open-source and vendor-provided AI models
• High proficiency in Python, APIs,and common AI/ML frameworks such as PyTorch, TensorFlow, HuggingFace, and LangChain.
• Experience supporting cloud-agnostic AI/ML platforms (training, deployment, MLOps) leveraging solutions such as Azure Foundry, AWS Bedrock, Ollama, or Vertex AI.
• Solid understanding of CI/CD pipelines, DevOps practices, and container engineering (Kubernetes/Docker).
• Strong understanding of AI ethics, data governance principles, and their application within an academic or public sector context.
• Excellent problem-solving, collaboration, and communication skills, including the ability to translate requirements into implemented solutions.

Assets (Nonessential)

• Knowledge of data sovereignty and privacy regulations relevant to Canadian higher education.
• Contributions to open-source AI projects or active engagement in the AI engineering community.
• Experience with ITSM platforms (e.g., ServiceNow) and workflow automation.

To Be Successful In This Role You Will Be

• Decisive
• Self-driven
• Efficient
• Organized
• Proactive
• Innovative

Please note: This is a new position.

A copy of the detailed position description is available to USW employees upon request to the Operations and Real Estate Partnerships Office.

Closing Date: 03/17/2026, 11:59PM ET

Employee Group: USW

Appointment Type: Budget - Continuing

Schedule: Full-Time

Pay Scale Group & Hiring Zone

USW Pay Band 18 -- $116,547. with an annual step progression to a maximum of $149,043. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol.

Job Category: Information Technology (IT)

Recruiter: Khristen Sivaramalingam

Lived Experience Statement

Candidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position.

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Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.

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