Remote Position: Hybrid Region: Americas Country: Canada State/Province: Ontario City: Toronto Project Objectives & Role Summary

The

AI DevOps 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 DevOps 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

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.

Secure DevOps & 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 GitHub).

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 DevOps administrators to embed automated vulnerability checks, binary scanning, and AI-assisted testing steps in Azure DevOps, Jenkins, and GitHub pipelines.

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.

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, DevOps, Cloud Engineering, or equivalent technical experience.

4+ years of hands-on experience in DevOps, 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 controls (Zscaler ZTNA, enterprise Firewalls).

Containerization & Orchestration: Strong proficiency with Docker, docker-compose, and Kubernetes to deploy scalable sandbox services.

Code Assist Integration: Familiarity with the configuration of developer-focused AI integrations like Claude Code, Gemini Antigravity inside Linux CLI environments.

Automation & Scripting: Solid scripting abilities in Python (specifically utilizing AI/ML libraries, request handling, and GCP SDKs) and Bash.

Preferred Certifications

Linux Enterprise Red Hat (RHCE / RHCSA)

GCP/AWS Engineering

Certified Kubernetes Administrator (CKA)

HashiCorp Certified: Terraform Associate

Working Style & Competencies

Diagnostic Mindset: Exceptionally strong debugging skills for networking, package distribution, and cloud service interconnections.

Proactive Collaboration: Able to work cr

📌 AI DevOps Specialist (Toronto)
🏢 Celestica
📍 Toronto