Data Security Engineer

General Intuition

$130K — $155K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in cloud security, specifically securing GCP and Kubernetes environments.
  • Proficient in threat modeling and incident response practices.
  • Experience with infrastructure as code (IaC) using Terraform for security configurations.
  • Familiarity with data protection techniques including encryption and access management.
  • Practical knowledge of CI/CD pipelines and security tooling integration.

Responsibilities

  • Harden cloud environments by implementing secure configurations and practices.
  • Protect data pipelines through encryption and logging mechanisms.
  • Manage identity and access controls to ensure least privilege access.
  • Secure software supply chains by scanning builds and dependencies.
  • Conduct operational security programs, including red-team exercises and incident response.

Benefits

  • Flexible work schedule to promote work-life balance.
  • Professional development opportunities through training and mentorship.
  • Health and wellness benefits to support employee well-being.
  • Collaborative work environment that encourages innovation.
  • Remote work options to foster a diverse workforce.
Full Job Description
The Role

This role secures the infrastructure bridging GI's AI research and Medal's creator platform. You will harden our cloud environments, protect our data pipelines, and ensure our deployment systems are safe from supply-chain attacks and other threats.

You'll design secure-by-default foundations without slowing down research or product teams, blending off-the-shelf security tooling with custom guardrails where necessary. Your work directly reduces operational risk across both General Intuition and Medal.
What We're Looking For
  • You harden GCP (AWS equivalents fine), Kubernetes, and containers from the inside out - workload isolation, network segmentation, IAM discipline, and secure-by-default guardrails baked into Terraform, CI/CD, and deployments.
  • You protect the data pipelines - encrypting and isolating the video/metadata ETL, with full logging and observability (Cloud Logging, SIEM, OpenTelemetry, Honeycomb) into how AI training data moves and is used.
  • You own identity, access, and secrets - privileged-access visibility, key rotation, least-privilege baselines, workload identity, and PKI (cloud-native KMS / Secret Manager).
  • You secure the software supply chain - scanned builds and dependencies, artifact provenance, hardened GitHub Actions runners.
  • You run the op-sec program - threat modeling, red-team and tabletop drills, incident response, and external pen-tests.
  • You keep us compliant across creator data and AI training data.
Our Stack

Cloud: GCP (GKE, Cloud Run, Cloud SQL, GCS, Pub/Sub, BigQuery), Cloudflare + Akamai edge • IaC & CI/CD: Terraform, GitHub Actions • Identity & secrets: Cloud IAM, workload identity, KMS / Secret Manager • Observability: Cloud Logging, SIEM, OpenTelemetry, Honeycomb

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