Platform Engineer

We are seeking a highly progressive Platform Engineer specializing in AI infrastructure and agentic execution environments to join our core cloud enablement team in Vancouver. In this role, you will bridge the gap between traditional Site Reliability Engineering (SRE) and cutting-edge Agentic AI operations. You will design, build, and operate secure multi-cloud landing zones, developer "golden paths," and reusable automated frameworks that empower application teams to safely deploy AI agents at scale.

This role is tailored for an engineer with a deep passion for automation, policy-as-code, and distributed systems. You will play a foundational role in defining how our enterprise architecture orchestrates, monitors, and secures large language model (LLM) agent frameworks, runtime function calling, and automated failover mechanics for high-volume retail environments.

Location:

Vancouver, BC (Hybrid – 4 days per week onsite)

Contract Duration: 6-month contract with high likelihood of extension

Advantages
Pioneering Technical Landscape:
Lead the implementation of modern agentic platform engineering frameworks for a world-renowned brand.

Elite Multi-Cloud Exposure:
Deepen your infrastructure mastery by operating simultaneously across production AWS and Azure environments.

High Extensibility Indicators:
Enter an initial 6-month contract with highly anticipated ongoing extension cycles as the AI platform grows.

Premier Workspace:
Collaborate within a dynamic, culture-led, and people-first onsite setting in Vancouver.

Responsibilities
1. AI Platform Delivery & Agentic Orchestration
Agentic Tool Enablement:
Build integration patterns, API mediation layers, and approval workflows supporting autonomous AI agent tool execution and runtime function calling.

Observability Ingestion:
Integrate advanced distributed telemetry for agent runs (execution traces, evaluation metrics, latency logs, and token cost analytics).

Failover & Guardrails:
Establish runtime safety controls for AI applications, embedding automated rollback scripts, cost control ceilings, and master kill-switches.

Landing Zone Architecture:
Build and scale highly secure, automated multi-cloud landing zones (AWS and Azure) utilizing reusable Terraform modules.

CI/CD Pipeline Engineering:
Construct and maintain robust Git Lab CI/CD pipelines, package registries, and automated infrastructure release strategies.

2. Security, Policy-as-Code & SRE Controls
Policy-as-Code Enforcements:
Implement strict automated infrastructure guardrails using Open Policy Agent (OPA), Conftest, or Azure Policies to guarantee security without breaking developer velocity.

Security Architecture:
Embed least-privileged access, zero-trust network segmentation, private endpoints, KMS encryption keys, and advanced secrets management.

SRE Practices:
Champion Site Reliability Engineering standards by managing Service Level Objectives (SLOs), calculating error budgets, configuring autoscaling matrices, and leading chaos engineering simulations.

Fin Ops Optimization:
Apply cloud financial management protocols (structured resource tagging, budget alarms, anomaly detection, and cluster right-sizing).

3. Developer Enablement & Community Support
Golden Path Documentation:
Author clear, accessible developer guides and self-service templates that streamline the adoption of core AI platform features.

Incident Response:
Form part of a formal production on-call rotation, managing real-time incident resolution and driving exhaustive post-mortem evaluations.

Qualifications
Must-Have Technical Skills
Core

Experience:

3–5 years of dedicated cloud platform engineering or SRE experience working with high-volume distributed systems natively in AWS and Azure.

Infrastructure as Code:
Elite proficiency with Terraform, with an emphasis on creating modular, reusable code structures and multi-environment pipelines.

Runtime

Languages:

Coding proficiency in Python or Go, with a solid history of integrating with complex REST/JSON APIs.

CI/CD & Containers:
Strong operational working knowledge of Git Lab CI/CD, Docker containerization, and cloud orchestration layers.

AI & Agentic Literacy:
Proven, hands-on exposure to AI/LLM…