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AI DevOps Specialist (AI Enablement & Secure DevOps)
Date: Sep 21, 2026
Location: Toronto, ON, CA
Project Objectives & Role Summary
The AI DevOps Specialist is primarily responsible for the technical deployment, secureenablement, administration, and continuous optimization of Celestica’s global HPS ArtificialIntelligence (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 cloud services (primarily Google Cloud Platform - Vertex AI), managing user-facing web interfaces (LibreChat or Gemini Enterprise Agent Platform), implementing agentic workflow architectures (Flowise AI or Gemini Enterprise Agent Platform), ensuring secure, uninterrupted developer access to AI coding assistants (such as Claude Code, Gemini Code Assist, and Claude Sonnet/Opus models), and establishing robust cloud budget governance.
Core Responsibilities & Scope of Work
- Multi-Phase Sandbox Rollout: Own the deployment and lifecycle management of the HPS AI Sandbox environment across cloud and hybrid infrastructures.
- Front-End User Interfaces: Deploy, configure, and maintain LibreChat (or similar web-based interfaces) to provide HPS engineers with safe, compliant, and localizedaccess to LLMs.
- Agentic Frameworks: Establish and configure Flowise AI or Gemini Enterprise AgentPlatform for the design and orchestration of agentic AI workflows and LLM-backedapplications.
- Model Registry & Endpoints: Administer model deployment, model endpointconfigurations, and vector databases within the sandbox environment.
- Project Governance: Oversee the HPS-designated GCP AI projects (e.g., gcp-ai-hps),including security permissions, service accounts, and IAM roles.
- Model Enablement & Quota Tuning: Coordinate the provisioning and scale-out ofadvanced foundational models (including Anthropic Claude 3.5/3.6/3.7 suite (Opus,Sonnet, Haiku) and Google Gemini) in Vertex AI. Actively manage, troubleshoot, andresolve API quota restrictions with cloud providers.
- Local Code Integration: Ensure developer command-line interfaces and localdevelopment terminals (such as Claude Code, VS Code, and GitKraken) seamlesslycommunicate with cloud model endpoints.
- Lab Network Troubleshooting: Diagnose and resolve intermittent connection issuesbetween HPS Design Labs (such as the Innovation Lab) and external AI resources or coderepositories (e.g., troubleshooting DNS, routing timeouts, and SSL inspection blocks onGitHub).
- Traffic Rules & Proxy Controls: Partner with Network Security to define, test, andtroubleshoot Zscaler ZTNA app connectors, firewall rules, and proxy exceptions necessaryto enable secure outbound AI API traffic while protecting proprietary codebase egress.
- CI/CD Integration: Work alongside DevOps administrators to embed automatedvulnerability checks, binary scanning, and AI-assisted testing steps in Azure DevOps,Jenkins, and GitHub pipelines.
4. Cloud Budget Governance & Financial Controls
- Cost Allocation & Monitoring: Design and implement rigid budget monitoring,consumption alerts, and cost-attribution controls in GCP to track HPS developer usage.
- Usage Auditing: Develop weekly/monthly utilization dashboards to track API tokenconsumption, model call costs, and sandbox compute runtimes.
- ROI Optimization: Provide recommendations on token limits, model pruning, caching strategies, and model choice (e.g., optimizing workloads to use Haiku or Flash models where appropriate to conserve budget).
5. AI Security, IP Protection & Compliance
- Data Sovereignty Compliance: Enforce enterprise policies ensuring that no proprietaryhardware schematics, PCB layouts, firmware source code, or IP are ingested into publictraining models.
- Evaluation & Testing: Support the isolation of the HPS Innovation Lab to evaluate newopen-source models, libraries, and AI security evaluation tools prior to general HPS rollout.
Education & Experience
- Bachelor’s degree in Computer Science, Software Engineering, DevOps, CloudEngineering, 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.
Required Technical Skills
- Cloud Platform Expertise (GCP): Advanced experience with Google Cloud Platform(GCP) and specifically Vertex AI / Model Garden, IAM, billing alerts, and VPC setups.
- AI Toolchain & LLM Tooling: Proven experience deploying and maintaining containerizedLibreChat architectures, Flowise AI (or LangChain/LlamaIndex equivalents), andlocal/cloud LLM APIs.
- Networking & Security Engineering: Solid understanding of enterprise networkingprotocols (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 AIintegrations like Claude Code, Gemini Code Assist, or MSFT Copilot CLI inside Linux/Macenvironments.
- Automation & Scripting: Strong scripting abilities in Python (specifically utilizing AI/MLlibraries, request handling, and GCP SDKs) and Bash.
Preferred Certifications
- Google Cloud Professional Machine Learning Engineer
- HashiCorp Certified: Terraform Associate
- Diagnostic Mindset: Exceptionally strong debugging skills for networking, packagedistribution, and cloud service interconnections.
- Proactive Collaboration: Able to work cross-functionally with HPS Hardware DesignTeams, Enterprise IT, Corporate Security, and external consulting suppliers (e.g., Elastify).
- Detail‑Oriented Documentation: High commitment to writing complete, clear StandardOperating Procedures (SOPs), system topologies, and budget management guidelines.
Physical Demands
The stated range includes Base Salary and target Short-Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range.
The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.
109,000 - CAD 173,000
Notes
This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.
Celestica is an Equal Opportunity Employer. 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.
At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. 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.