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Platform Engineer - AI/ML Infrastructure
- Toronto, ON, Canada
Full-time
This opening has closed.
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Job details
- Job type
- Full-time
- Closing date
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Platform Engineer - AI/ML Infrastructure
Full Time
Toronto, ON (Hybrid-4 days onsite per week)
Roles and responsibilities:
- Were seeking a skilled Platform Engineer to deploy and manage our AI/ML infrastructure, e.g LlamaIndex Cloud and KDB.AI applications on Kubernetes Platform.
- Youll be responsible for building reliable, scalable, and secure deployment pipelines using modern GitOps practices.
- Deploy and manage LlamaIndex Cloud and KDB.AI applications and similar products supporting AI workloads across Dev/QA/Prod environments
- Implement GitOps workflows using Flux CD for automated deployments
- Administer Kubernetes clusters across multiple environments
- Configure HashiCorp Vault for secrets management and ExternalSecrets integration
- Maintain CI/CD pipelines with GitHub Actions and Artifactory
- Work with enterprise Identity Management team to configure OIDC authentication with Microsoft Entra ID
- Create and maintain Helm charts and Kubernetes manifests
- Monitor application performance and troubleshoot production issues
- Document procedures, runbooks, and infrastructure patterns
Required Skills
- Core Technologies:
- 3+ years managing production Kubernetes clusters
- 2+ years with Flux CD, ArgoCD, or similar GitOps tools
- Advanced Helm chart development and management
- HashiCorp Vault for secrets management
- Artifactory or similar container registries
- CI/CD with GitHub Actions, Jenkins, or similar
- Infrastructure & Database:
- PostgreSQL, MongoDB, Redis, RabbitMQ administration
- Database HA/failover configurations (PgBouncer, HAProxy)
- Linux/Unix systems and shell scripting (Bash, PowerShell)
- Kubernetes networking, Ingress, and Gateway API
Nice to Have:
- Experience with LlamaIndex, LangChain, or AI/ML platforms
- Vector databases or KDB.AI knowledge
- Temporal.io workflow orchestration
- Python/Go for automation
More about this job
Responsibilities
Deploy and manage AI/ML applications and Kubernetes infrastructure across development, QA, and production environments, building reliable and secure deployment pipelines with GitOps practices. Administer clusters, secrets management, CI/CD, identity integrations, and monitoring, while documenting procedures and troubleshooting production issues.
Requirements
Requires at least three years managing production Kubernetes clusters and at least two years using Flux CD, Argo CD, or similar GitOps tools, along with advanced Helm, Vault, CI/CD, and container registry experience. Also requires experience with databases and high availability, Linux/Unix and shell scripting, and Kubernetes networking; AI/ML platforms, vector databases, Temporal.io, and Python or Go are advantageous.
Skills
- Kubernetes
- Flux CD
- GitOps
- Helm
- HashiCorp Vault
- Artifactory
- GitHub Actions
- PostgreSQL
- MongoDB
- Redis
- RabbitMQ
- Linux/Unix
- Shell Scripting
- Kubernetes Networking
- LlamaIndex
- KDB.AI
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
Keywords
- AI/ML Infrastructure
- Kubernetes
- LlamaIndex Cloud
- KDB.AI
- GitOps
- Flux CD
- Argo CD
- HashiCorp Vault
- ExternalSecrets
- GitHub Actions
- Artifactory
- Microsoft Entra ID
- OIDC
- Helm Charts
- Kubernetes Manifests
- PostgreSQL
- MongoDB
- Redis
- RabbitMQ
- PgBouncer
- HAProxy
- Linux/Unix
- Bash
- PowerShell
- Ingress
- Gateway API
- LangChain
- Vector Databases
- Temporal.io
- Python