Cartography Biosciences

Cartography Biosciences

DevOps Engineer, Cloud Infrastructure & Scientific Computing (Remote, Americas)

Remote (United States)

Sponsorship not specifiedDetected 14 days ago
PythonGitAWSGCPCloud PlatformsTerraformCI/CDGitHub ActionsLinuxDevOpsSite Reliability EngineeringMachine LearningAI OrchestrationCybersecurityIncident ResponseComplianceLogisticsHIPAABioinformaticsResearchCommunicationCollaboration

About the role

  • This role sits at the intersection of cloud engineering, scientific computing, and applied software development.
  • This role is 100% remote and can be based in the US, Canada, Mexico, Central America, or South America.

Responsibilities

  • Architect, deploy, and maintain cloud infrastructure across Google Cloud Platform (primary) and AWS (secondary), with a focus on cost efficiency, reproducibility, and security across compute, storage, networking, and identity.
  • Manage infrastructure-as-code using Terraform, with full version control via GitHub and CI/CD pipelines that support both scientific compute and internal application deployment.
  • Maintain uptime, observability, and incident response for internal applications including Slack integrations, web dashboards, and data ingestion services that connect lab and computational workflows.
  • Implement and uphold data security practices appropriate for a biotech environment, including IAM, secrets management, audit logging, network segmentation, and compliance-adjacent controls.
  • Collaborate with computational biologists and software engineers to operationalize new tools and pipelines, translating prototype workflows into reliable production systems.

Requirements

  • DevOps Engineer: 4+ years of hands-on DevOps, SRE, or cloud infrastructure experience.
  • Strong production experience with Google Cloud Platform (GCE, GKE, GCS, Cloud Run, IAM, Cloud Logging, Batch) and working knowledge of AWS (EC2, S3, IAM, Lambda).
  • Deep proficiency with Terraform, GitHub Actions or equivalent CI/CD systems, and Docker.
  • Proficiency in Python for scripting, automation, and data handling
  • 4+ years of hands-on DevOps, SRE, or cloud infrastructure experience.

Nice to have

  • Experience supporting scientific or research computing environments (genomics, single-cell, structural biology, ML, or HPC).
  • Familiarity with workflow orchestration systems such as Cromwell, Nextflow, WDL, or Airflow.
  • Experience with GPU infrastructure and scheduling of ML or protein design workloads.
  • Background in life sciences infrastructure, including familiarity with Benchling, ELN integrations, or scientific data management systems.
  • Prior experience at an early-stage biotech, scientific software company, or research-driven startup.
  • Familiarity with SOC 2, HIPAA-adjacent, or other regulated-environment security frameworks.
  • You will report directly to the head of computational biology.
  • Compensation calibrated to local market with US benchmarking Direct collaboration with our US-based engineering and computational biology teams in South San Francisco.

Skills

  • Triage and resolve infrastructure issues across the stack, with clear documentation and post-mortems that improve the system over time.
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This listing is sourced directly from Cartography Biosciences's careers page and normalized into a canonical job model.