Senior Platform Engineer – Cloud Architecture, AI Platforms

Derivative Path

Senior AI Platform Engineer responsible for AWS infrastructure design and DevOps practices at a fintech company. Collaborating with AI teams, ensuring reliable and scalable AI workloads.

Posted 5/22/2026full-timeRemote • 🇨🇦 CanadaSenior💰 CA$110,000 - CA$140,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerEC2KubernetesPostgresPythonTerraform

About the role

Key responsibilities & impact

Design and own AWS multi-account architectures, including VPC networking, security controls, and shared-services patterns to support AI workloads
Build and maintain scalable compute environments using ECS Fargate, EKS, and Lambda for both application and model hosting
Implement Infrastructure as Code (IaC) using AWS CDK (preferred) or Terraform to define and manage the entire AI platform stack
Develop and manage CI/CD pipelines using GitHub Actions, incorporating blue/green and canary strategies for model deployments
Architect and operate data services including RDS (Aurora), S3, and Vector Databases (e.g., Pinecone, pgvector) to support RAG and other AI patterns
Partner with the AI Innovation Group to operationalize models using AWS SageMaker, Bedrock, and Azure OpenAI Service
Implement comprehensive observability for infrastructure and model performance, monitoring for latency, drift, and resource utilization
Ensure platform resilience and security, defining disaster recovery strategies and enforcing strict IAM policies for sensitive data.

Requirements

What you’ll need

5+ years of experience in DevOps, Platform Engineering, or Cloud Infrastructure
Deep expertise in AWS core services (EC2, VPC, IAM, S3) and networking (Transit Gateways, Route 53)
Strong proficiency in Infrastructure as Code, specifically AWS CDK or Terraform
Experience with container orchestration (Kubernetes/EKS or ECS) and Docker
Proficiency in Python for scripting and automation; experience with API frameworks (FastAPI) is a plus
Familiarity with MLOps practices and tools (SageMaker, MLflow, Kubeflow) and deploying LLMs in production
Experience designing CI/CD pipelines (GitHub Actions) for both code and data/model workflows
Understanding of database architecture, including relational (PostgreSQL) and vector stores
Bachelor’s degree in computer science, Engineering, or equivalent practical experience.

Benefits

Comp & perks

Competitive bonus, base salary, and equity compensation
23 days of PTO
Fully remote
RRSP contribution at 3%
Competitive health benefits

ATS Keywords

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Hard Skills & Tools

AWSInfrastructure as CodeAWS CDKTerraformCI/CD pipelinesPythonKubernetesECSDockerdatabase architecture

Certifications

Bachelor’s degree in computer scienceBachelor’s degree in Engineering