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Added 39 mins ago
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Design Verification Engineer (PCIe)
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Canada
- Full-time
🚀 Hiring: Design Verification Engineer (PCIe) | Canada
Added 39 mins ago
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Senior Silicon ML Engineer
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…nexus of silicon design and machine learning. As a Silicon ML Engineer on our team, you’ll fuse knowledge of chip design and ML into end-to-end silicon design flows. If you thrive on…
Added 54 mins ago
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Development Ops Engineer
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This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Development Ops Engineer based in Canada.
Added 1 hour ago
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Senior Software Engineer
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Ingénieur de données senior
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Salesforce Release Engineer
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Spécialiste Qualité Fournisseurs
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Analog Engineer, Staff
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- Full-time
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Added 3 hours ago
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Android & Robotics Software Developer
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Founding Engineer, Build and Deployment
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Added 3 hours ago
Designer- 12-month term
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Added 3 hours ago
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Senior AI Developer
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Toronto, ON · Greater Toronto and Hamilton Area, ON
- Other
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Added 4 hours ago
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Senior Supplier Quality Engineer
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Insight Global

Principal Platform Engineer

Vancouver, BC, Canada

Expected salary starting at $200,000 · Full-time

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Job details

Pay: Expected salary starting at $200,000
Job type: Full-time
Apply by: Dec 2, 2026
Experience: 10+ years of experience across platform engineering, cloud infrastructure, software engineering, or enterprise architecture
Posting language: English
Posted: Nov 2, 2026

Original job description

Job Description

Insight Global is seeking a Principal Platform Engineer for a global retailer to take technical ownership of and scale an enterprise AI platform within GCP.

This is a senior individual contributor role with no direct reports, though this person will provide technical leadership and mentorship to engineering teams. The ideal candidate has personally built and operated enterprise AI/ML platforms in production, specifically within GCP and Vertex AI, and can own critical platform architecture decisions.

Responsibilities:

Own and evolve the enterprise AI platform architecture within GCP
Build and scale Vertex AI MLOps capabilities, including training pipelines, Model Registry, evaluation/approval workflows, and model serving
Establish MLOps/LLMOps standards across development, deployment, monitoring, and lifecycle management
Build GenAI platform capabilities including RAG, grounding, prompt management, guardrails, evaluations, agents, and MCP integration
Develop reusable Terraform modules, Infrastructure-as-Code, policy-as-code, and CI/CD pipelines
Create self-service “golden path” templates for engineering teams
Implement AI/ML observability and FinOps practices, including tracing, drift detection, latency, token usage, and cost monitoring
Establish platform standards around security, governance, scalability, and responsible AI
Remain hands-on with Python while owning key architecture decisions
Provide technical leadership and mentorship across engineering, data, architecture, security, and product teams

Required Skills & Experience

10+ years of experience across platform engineering, cloud infrastructure, software engineering, or enterprise architecture
Proven experience building and operating enterprise AI/ML platforms in production
Deep hands-on expertise with GCP and Vertex AI
Strong experience with MLOps and LLMOps architecture
Vertex AI experience across training pipelines, Model Registry, evaluation/approval, and model serving
GenAI experience with RAG, grounding, guardrails, evaluations, agents, and/or MCP
Strong Terraform, Infrastructure-as-Code, policy-as-code, and CI/CD experience
Experience building reusable/self-service platform capabilities for other engineering teams
Experience with AI/ML observability and FinOps
Advanced Python software engineering skills
Ability to independently own major platform architecture decisions

Pay Transparency:

Expected salary starting at $200,000

Vacancy Disclosure:

This role is for a new vacant opening within a growth project.

Please note, artificial intelligence tools are used to assist in screening and assessing applicants for this position.

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More about this job

Responsibilities

Own and evolve the enterprise AI platform architecture in GCP, building Vertex AI MLOps capabilities and GenAI features such as RAG, guardrails, evaluations, and agents. Develop reusable infrastructure and self-service templates, establish observability, FinOps, security, and governance standards, and provide hands-on technical leadership and mentorship.

Requirements

Requires 10+ years of experience in platform engineering, cloud infrastructure, software engineering, or enterprise architecture, with proven experience operating production enterprise AI/ML platforms. Candidates need deep GCP and Vertex AI expertise, strong MLOps/LLMOps and GenAI experience, Terraform and CI/CD skills, advanced Python ability, and the capacity to own major architecture decisions.

Skills

GCP
Vertex AI
MLOps
LLMOps
Generative AI
RAG
Terraform
Infrastructure As Code
Policy As Code
CI/CD
Python
AI/ML Observability
FinOps
Model Serving
Platform Architecture
Technical Leadership

Visa sponsorship

Not detected in the job text

Keywords

GCP
Vertex AI
Enterprise AI Platform
AI/ML
MLOps
LLMOps
Training Pipelines
Model Registry
Model Serving
Generative AI
RAG
Grounding
Prompt Management
Guardrails
Evaluations
AI Agents
MCP Integration
Terraform
Infrastructure As Code
Policy As Code
CI/CD
Python
AI/ML Observability
FinOps
Drift Detection
Responsible AI
Cloud Infrastructure
Platform Engineering
Self-Service Templates
Security And Governance

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