DevOps Engineer, Cloud Infrastructure, Scientific Computing

🕒 July 28

🏈 North America – Remote

💵 $130k - $145k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 6%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Cartography Biosciences

WebsiteLinkedInAll Job Openings

11 - 50 employees

🧬 Biotechnology

💊 Pharmaceuticals

Biotechnology • Pharmaceuticals

Cartography Biosciences is a biotechnology company focused on discovering and characterizing tumor-selective antigens to enable safer, more precise cancer immunotherapies. Using single-cell genomics, proteomics, novel binder discovery, and computational analysis, Cartography builds a comprehensive antigen atlas across thousands of patient samples and millions of cells to evaluate antigen expression in tumors and normal tissues. The company aims to identify druggable, tumor-specific targets and develop therapeutics across multiple modalities (e. g. , T-cell engagers) to expand treatable cancers while minimizing off-tumor toxicity; it has collaborations and clinical-stage activity referenced in its public materials.

📋 Description

• 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. • Support and extend our scientific compute infrastructure, including Cromwell, Google Batch, Cloud Run, Cloud Storage, and GPU-accelerated environments for protein design, structural prediction, and machine learning workloads. • 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. • Triage and resolve infrastructure issues across the stack, with clear documentation and post-mortems that improve the system over time. • Articulate technical decisions and trade-offs to diverse audiences, including engineering and scientific teams.

🎯 Requirements

• 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; comfortable in Unix or Linux terminal environments. • Practical experience implementing data security controls, including encryption, access policies, secrets management, and audit trails. • Demonstrated ability to maintain internal-facing applications and services with high uptime expectations. • Excellent written and verbal communication in English, with the ability to document systems clearly for both engineers and scientists. • Working hours that include meaningful synchronous overlap with US Pacific Time.