Platform Engineer, Biotech

Department: Engineering

Location: San Francisco

Employment Type: FullTime

About the Role

Join a biotech AI team building data infrastructure that turns clinical, genomic, imaging, and other biomedical data into reliable, model-ready assets. You will help design and operate the platform, with a focus on secure, governed data systems and production infrastructure for scientific and machine learning teams.

What You'll Do

• Build and maintain cloud data platform components, including object storage, lakehouse architecture, catalogs, lineage, dataset versioning, and query and access layers.

• Design and operate data warehouses and governed systems for clinical records, molecular features, metadata, retention, and dataset releases.

• Develop reproducible bioinformatics workflows for omics data, using containerized pipelines and cloud batch compute.

• Implement data quality checks, biological validation, and visualizations that help teams identify issues across processing steps.

• Deliver versioned, training-ready datasets and data deployment interfaces for model use in partner environments.

• Operate production infrastructure, including Kubernetes, CI/CD, workload orchestration, security, reliability, observability, and cost optimization.

What We're Looking For

• Two to five years of experience building data infrastructure and production pipelines as a platform engineer in biotech, diagnostics, biobanking, health data, or a related field working with sensitive biological or clinical data.

• Production experience operating Kubernetes clusters, writing infrastructure as code with Terraform or similar tools, and shipping tested, documented Python and/or Go code.

• Experience designing CI/CD and deployment systems, orchestrating distributed workloads, and owning infrastructure reliability, observability, security, and cost.

• Familiarity with a major cloud provider, preferably AWS, plus Docker, workflow managers such as Nextflow, lakehouse and warehouse design, data catalogs, and orchestration.

• Experience with large-scale data pipelines, machine learning infrastructure, or GPU workloads is valuable. Knowledge of omics workflows, bioinformatics tools, OMOP, FHIR, R, or SQL is also relevant.

• Experience implementing compliance controls and audit evidence for standards such as HIPAA, GDPR, or SOC 2 is beneficial.

Compensation & Benefits

Base salary: $180,000 to $240,000 annually. Visa sponsorship is not available.

Location

Hybrid role based in San Francisco, California. Candidates must be local or willing to relocate.