AI Infrastructure Engineer

Toronto, Ontario, CanadaOnsiteFull TimePosted 2 months ago

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Role summary

We are seeking an AI Infrastructure Engineer to build and manage our internal, on-premises AI platform, the JRoberts Sustainment Intelligence Platform (JSIP). This role is crucial for securely indexing, analyzing, and operationalizing internal data to support engineering, proposal development, and knowledge management. Responsibilities include deploying AI servers, developing AI tools like document search and RAG-based applications, structuring data, and maintaining system performance. The ideal candidate will have experience with Linux, Docker, LLM/RAG architectures, graph databases (Neo4j), and Python for machine learning projects, demonstrating strong technical growth potential in applied AI.

We are hiring an
AI Infrastructure Engineer
to lead the development and operation of our internal AI platform.

This role will focus on building and maintaining a secure, on-premises system that supports engineering, sustainment programs, proposal development, and enterprise knowledge management across the organization.

The
JRoberts Sustainment Intelligence Platform (JSIP)
is a private, on-premises AI system designed to securely index, analyze, and operationalize internal data.

The platform enables teams to:

Search and retrieve technical records efficiently
Generate structured outputs for engineering and program workflows
Support activities such as RCE preparation, technical investigations, and proposal development
Improve consistency and speed in decision-making across the business

Unlike public AI tools, JSIP operates entirely within our internal environment, ensuring full control over sensitive data while enabling advanced AI-driven capabilities.

This platform is being developed as a core internal capability and will play a key role in how we support programs, manage knowledge, and engage with partners. The AI Infrastructure Engineer will be central to scaling and evolving this system as part of our broader technology strategy.

Responsibilities:

Deployment and operation of our new rack-mounted AI server
Development of an internal AI knowledge platform (document search, technical lookup, RAG-based tools)
Structuring and indexing engineering and sustainment data
Supporting departments with AI-enabled research, drafting, and information retrieval
Maintaining system performance, backups, and basic infrastructure monitoring
Working closely with engineering, operations, and program teams to translate workflows into AI tools

Qualifications:

Computer Engineering degree
Hands-on experience with Linux environments
Experience with Docker and containerized deployments
Exposure to LLM and RAG architectures
Graph database experience (Neo4j)
Python and machine-learning project experience
Strong technical growth potential and interest in applied AI systems

This is a foundational hire for our internal digital capability and will support long-term operational efficiency across the business.

John Gagliardi

Gerry Mandarello;

Human Resources

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