Senior Cloud / Data Engineer (Data / Reconstruction / HIPAA)

Location: San Francisco

WHAT YOU'LL DO

1. Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably.

2. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls.

3. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility.

4. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews.

5. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet.

WHAT WE'RE LOOKING FOR

- Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability.

- Experience shipping production systems that handle large data volumes and failure-prone networks.

- Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments.

USEFUL EXPERIENCE

- Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability.

- Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails.

- Owning the 'boring' backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks.

- Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

Responsibilities

Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably; Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls; Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility; Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews; Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet.

Requirements

Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability; Experience shipping production systems that handle large data volumes and failure-prone networks; Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments.

Nice to have

Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability; Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails; Owning the 'boring' backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks; Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.