Platform Engineer

About Limina Limina is the contextual data intelligence platform built for the AI era. Evolved from Private AI, the world's most accurate PII and PHI de-identification engine, Limina has expanded into a full platform play that governs sensitive data across the entire enterprise AI lifecycle: from classification and redaction through to agentic workflows, RAG pipelines, and real-time data security. Brands like RBC, Deepgram, and Boehringer Ingelheim already rely on our platform to build on, govern, and deploy AI against their most sensitive datasets. We've been recognized as a Gartner® Cool Vendor™ in Privacy and a World Economic Forum Technology Pioneer, and we’re backed by investors in Toronto, New York, Seattle, and San Francisco. What You'll Do You will be a part of a team that designs, builds, and maintains customer deployment tooling. Our core machine learning product requires highly performant and stable infrastructure and our customers require that infrastructure to be composable, secure, scalable, and monitored. Additionally you will help to keep Limina critical infrastructure available, such as license verification and metering services. Areas of Focus Building and maintaining a collection of helm charts, kubernetes artifacts, and associated training materials Working closely with Solutions Engineering, turning customer-focused prototypes and tools into production-grade products Building and maintaining critical services and infrastructure Maintain platform marketplaces for SaaS vendors such as AWS, Azure, and Snowflake What You Bring 3 - 5 years of engineering experience building products, infrastructure, and automation Experience building with a focus on security, reliability, scalability, and maintainability Operational experience with one or more: Kubernetes, Helm, Docker, etc Terraform, Ansible, Cloudformation, etc Python, Typescript, etc AWS, Azure, GCP, etc Strong communicator, both written and verbal Nice to Have Experience in fintech, compliance, or regulated-industry customer environments Prior experience in a customer-facing role Early-stage startup experience

You will design, build, and maintain customer deployment tooling and critical infrastructure for a machine learning platform. This includes managing Kubernetes artifacts, maintaining SaaS marketplaces, and ensuring the reliability and security of production-grade services.

The ideal candidate has 3-5 years of engineering experience with infrastructure, automation, and cloud platforms. Strong operational experience with Kubernetes, Helm, and infrastructure-as-code tools is required, along with excellent communication skills.

• Microsoft AzurePreferred
• KubernetesPreferred
• DockerPreferred
• TypeScriptPreferred
• Amazon Web ServicesPreferred
• Google CloudPreferred
• TerraformPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Kubernetes
• Helm
• Docker
• Terraform
• Ansible
• Cloudformation
• Python
• Typescript
• AWS
• Azure
• GCP
• Infrastructure as Code
• Automation
• SaaS
• Security
• Scalability
• Pipelines
• Financial Technology (FinTech)
• Workflow Management
• AWS CloudFormation
• Snowflake (Data Warehouse)
• Helm (Software)
• Artificial Intelligence
• Amazon Web Services
• Microsoft Azure
• Customer Service
• Software As A Service (SaaS)
• Data Intelligence
• Python (Programming Language)
• Machine Learning
• Maintainability
• Tooling
• TypeScript
• Reliability
• Real Time Data
• Docker (Software)

• Technology
• Software
• Engineering
• Data & Analytics
• Security & Safety
• Platform Engineer
• Software and Applications Developers and Analysts Not Elsewhere Classified
• Validation Engineers
• Industrial Engineers

Minimum experience

2+ years

Posting language

English

Working hours

40 hours per week