Tobogganlabs

Tobogganlabs

Développeur·se senior en sécurité des plateformes - Senior Platform Security Developer

Montréal, Quebec, Canada · Senior

Sponsorship not specifiedDetected 44 days ago
PythonBashGitAWSAzureCloud PlatformsKubernetesTerraformCI/CDGitHub ActionsDevOpsSOC OperationsComplianceCadenceHIPAALeadershipCommunicationMentoringPublic SpeakingAdaptability

About the role

  • This position combines deep expertise in cloud infrastructure and DevOps practices with hands-on security engineering, particularly in identity management and endpoint security.
  • Note that while we specialize in healthcare and regulated industries, not all our projects are in these fields, so you may work across different domains from time to time.
  • On some projects, you'll focus purely on infrastructure work without a security emphasis-this is a consultancy, and client needs vary.

Nice to have

  • Budget pour le bureau à domicile et la technologie;
  • Budget annuel de développement professionnel;
  • REER avec contribution de l'employeur après 1 an;
  • Assurance santé et dentaire payée à 100 % par l'employeur, incluant un montant annuel pour les soins complémentaires (acupuncture, ostéopathie, massothérapie, naturopathie, psychologie, etc.);
  • Assurance vie et assurance invalidité de courte et de longue durée;

Skills

  • Most of our clients use AWS, Terraform, GitHub Actions or similar CI/CD tools, and modern identity providers.

Company info

  • Toboggan Labs is a boutique consultancy building at the intersection of AI and healthcare.
  • We solve challenging human problems by applying cutting-edge technology and domain understanding.
  • We are seeking individuals with a strong track record of building and securing infrastructure in production environments.
  • We're seeking a senior platform security developer to help our clients build secure, compliant infrastructure that enables their teams to move fast without compromising on security.

This listing is sourced directly from Tobogganlabs's careers page and normalized into a canonical job model.