AI DevOps Specialist; AI Enablement & Secure DevOps Job Toronto Ontario Canada,IT/Tech

Position: AI DevOps Specialist (AI Enablement & Secure DevOps)

Remote Position:
Hybrid
Region:
Americas
Country:
Canada
State/Province:
Ontario
City:
Toronto

Project Objectives & Role Summary

The AI Dev Ops Specialist is primarily responsible for the technical deployment, secure enablement, administration, and continuous optimization of Celestica’s global HPS Artificial Intelligence (AI) sandbox, modeling, and software engineering toolchains.

This specialist will bridge the gap between AI development pipelines, secure networking infrastructure, and cloud platform services. They will take a hands-on lead in configuring foundational AI services within the Dev Ops space. implementing agentic workflow architectures, ensuring secure, uninterrupted developer access to AI coding assistants (such as Claude Code, Gemini Antigravity Code, and Codex), and establishing robust cloud governance.

Core Responsibilities & Scope of Work

1. AI Sandbox Platform Administration & Deployment

Multi-Phase Sandbox Rollout: Own the deployment and lifecycle management of the HPS AI Sandbox environment across cloud and hybrid infrastructures.

Agentic Frameworks: Establish and configure platforms such as Claude Code, Gemini Antigravity Code, and Codex for the design and orchestration of agentic AI workflows and LLM-backed applications.

Project Governance: Oversee the HPS-designated AI projects, including security permissions, service accounts, and IAM roles.

Model Enablement & Tuning: Coordinate the provisioning and scale-out of advanced foundational models. Actively manage, troubleshoot, and resolve API restrictions with cloud providers.

3. Secure Dev Ops & Network Integration (Zscaler & Firewall)

Lab Network Troubleshooting: Diagnose and resolve intermittent connection issues between HPS Design Labs (such as the Innovation Lab) and external AI resources or code repositories (e.g., troubleshooting DNS, routing timeouts, and SSL inspection blocks on Git Hub).

Traffic Rules & Proxy Controls: Partner with Network Security to define, test, and troubleshoot Zscaler ZTNA app connectors, firewall rules, and proxy exceptions necessary to enable secure outbound AI API traffic while protecting proprietary codebase egress.

CI/CD Integration: Work alongside Dev Ops administrators to embed automated vulnerability checks, binary scanning, and AI-assisted testing steps in Azure Dev Ops, Jenkins, and Git Hub pipelines.

4. Observiability and Monitoring Controls with AI

Monitoring: Design and implement rigid monitoring, consumption alerts, and attribution controls in all on-prem and virtualize all environments to track HPS developer usage.

Live Auditing: Develop real-time observability using AI dashboards to track consumption, model call costs, and sandbox compute runtimes.

5. AI Security, IP Protection & Compliance

Data Sovereignty Compliance: Enforce enterprise policies ensuring that no proprietary hardware schematics, PCB layouts, firmware source code, or IP are ingested into public training models.

Evaluation & Testing: Support the isolation of the HPS Innovation Lab to evaluate new open-source models, libraries, and AI security evaluation tools prior to general HPS rollout.

Education & Experience

Bachelor’s degree in Computer Science, Software Engineering, Dev Ops, Cloud Engineering, or equivalent technical experience.

4+ years of hands-on experience in Dev Ops, Cloud Engineering, or System Administration, with at least 2 years focused specifically on AI/MLOps platform delivery.

Knowledge/Skills/Competencies

Required Technical Skills

AI Toolchain & LLM Tooling:
Proven experience deploying and maintaining containerized mircoservices, and local/cloud LLM APIs.

Networking & Security Engineering:
Solid understanding of enterprise networking protocols (DNS, TCP/IP routing, NAT, SSL/TLS handshake) and secure access…