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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
Experience
10+ years of experience across platform engineering, cloud infrastructure, software engineering, or enterprise architecture
Posting language
English
Posted

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.

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

Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics
  • Consulting

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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