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About the Role

The AI DevOps Specialist is 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.

Responsibilities

Own the deployment and lifecycle management of the HPS AI Sandbox environment across cloud and hybrid infrastructures.
Deploy, configure, and maintain LibreChat (or similar web-based interfaces) to provide HPS engineers with safe, compliant, and localized access to LLMs.
Establish and configure Flowise AI or Gemini Enterprise Agent Platform for the design and orchestration of agentic AI workflows and LLM-backed applications.
Administer model deployment, model endpoint configurations, and vector databases within the sandbox environment.
Oversee the HPS-designated GCP AI projects (e.g., gcp-ai-hps), including security permissions, service accounts, and IAM roles.
Coordinate the provisioning and scale-out of advanced foundational models in Vertex AI.
Actively manage, troubleshoot, and resolve API quota restrictions with cloud providers.
Ensure developer command-line interfaces and local development terminals seamlessly communicate with cloud model endpoints.
Diagnose and resolve intermittent connection issues between HPS Design Labs and external AI resources or code repositories.
Define, test, and troubleshoot Zscaler ZTNA app connectors, firewall rules, and proxy exceptions necessary to enable secure outbound AI API traffic.
Work alongside DevOps administrators to embed automated vulnerability checks, binary scanning, and AI-assisted testing steps in CI/CD pipelines.
Design and implement rigid budget monitoring, consumption alerts, and cost-attribution controls in GCP to track HPS developer usage.
Develop weekly/monthly utilization dashboards to track API token consumption, model call costs, and sandbox compute runtimes.
Provide recommendations on token limits, model pruning, caching strategies, and model choice to conserve budget.
Enforce enterprise policies ensuring that no proprietary hardware schematics, PCB layouts, firmware source code, or IP are ingested into public training models.
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.

Requirements

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.
Advanced experience with Google Cloud Platform (GCP) and specifically Vertex AI / Model Garden, IAM, billing alerts, and VPC setups.
Proven experience deploying and maintaining containerized LibreChat architectures, Flowise AI (or LangChain/LlamaIndex equivalents), and local/cloud LLM APIs.
Solid understanding of enterprise networking protocols (DNS, TCP/IP routing, NAT, SSL/TLS handshake) and secure access controls (Zscaler ZTNA, enterprise Firewalls).
Strong proficiency with Docker, docker-compose, and Kubernetes to deploy scalable sandbox services.
Familiarity with the configuration of developer-focused AI integrations like Claude Code, Gemini Code Assist, or MSFT Copilot CLI inside Linux/Mac environments.
Strong scripting abilities in Python (specifically utilizing AI/ML libraries, request handling, and GCP SDKs) and Bash.
Exceptionally strong debugging skills for networking, package distribution, and cloud service interconnections.
Able to work cross-functionally with HPS Hardware Design Teams, Enterprise IT, Corporate Security, and external consulting suppliers.
High commitment to writing complete, clear Standard Operating Procedures (SOPs), system topologies, and budget management guidelines.

Skills

GCP
Vertex AI
Model Garden
IAM
Billing Alerts
VPC Setups
LibreChat
Flowise AI
LangChain
LlamaIndex
LLM APIs
Docker
docker-compose
Kubernetes
Claude Code
Gemini Code Assist
MSFT Copilot CLI
Python
Bash
Zscaler ZTNA
Enterprise Firewalls
DNS
TCP/IP routing
NAT
SSL/TLS handshake
Azure DevOps
Jenkins
GitHub

Location

Toronto, Ontario, Canada

Work Type

Remote
Hybrid

Experience Level

4+ years of hands-on experience in DevOps, Cloud Engineering, or System Administration
2+ years focused specifically on AI/MLOps platform delivery

Education Level

Bachelor’s degree in Computer Science, Software Engineering, DevOps, Cloud Engineering, or equivalent technical experience

Salary/Compensations

109,000 - CAD 173,000

Benefits

A comprehensive benefits package is offered in addition to this range.

About the Company

Celestica is an Equal Opportunity Employer.
At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported.

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.
Special arrangements can be made for candidates who need it throughout the hiring process. Please indicate your needs and we will work with you to meet them.