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 with GCP and Kubernetes
  • Proficient in Terraform and CI/CD processes
  • Demonstrated knowledge of IAM principles and privilege management
  • Experience with data encryption and secure data management practices
  • Familiarity with op-sec programs and incident response strategies
  • Understanding of cloud supply chain security and software vulnerabilities

Responsibilities

  • Harden cloud environments focusing on workload isolation and network segmentation
  • Protect data pipelines through encryption and comprehensive logging practices
  • Manage identity and access controls, ensuring least privilege access
  • Secure software supply chains by scanning builds and dependencies
  • Lead operational security programs, including threat modeling and incident response
  • Ensure compliance with standards concerning creator and AI training data

Benefits

  • Access to cutting-edge AI and cloud technologies
  • Opportunity to shape security frameworks from the ground up
  • Collaborative work environment bridging research and product teams
  • Professional development opportunities in security practices
  • Flexible work arrangements to support a healthy work-life balance
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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