Director, AI Governance & Security Architecture

Huron

United States

Remote

USD 190,000 - 265,000

Full time

14 days+
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Benefits offered by this job

Annual incentive
Medical benefits
Travel opportunities

Job summary

Huron is seeking an experienced Director-level AI Security professional in the United States to translate security, privacy, and architecture requirements into executable platform controls for AI workloads. You will define classification patterns, control sets, and audit evidence across the AI lifecycle, partnering with infrastructure teams to implement automated reporting and telemetry.

Join a role focused on governance engineering, evaluation patterns, and knowledge management for MVP

Qualifications

  • 8+ years in cloud security, governance or AI security fields.
  • Translate requirements into actionable engineering controls and metrics.
  • Strong data engineering, analytics or automation skills.
  • Demonstrated ability to build governance, dashboards and audit evidence.

Responsibilities

  • Translate security and architecture requirements into executable AI workload controls.
  • Define workload classifications and required controls for each class.
  • Establish data handling, logging, retention and redaction patterns with governance in mind.
  • Design audit evidence patterns for model access and operational events.
  • Develop identity, network, logging and approval-gate patterns for AI apps.
  • Create governance patterns for knowledge sources and retrieval evaluation.
  • Collaborate with infra to automate control design and reporting.
  • Ensure AI outputs are useful, grounded, auditable, and cost-effective.

Skills

Cloud security
Governance engineering
AI governance
Automation engineering
Observability
Policy to controls
Documentation

Tools

AWS Bedrock
AWS IAM
CloudTrail
CloudWatch
KMS
VPC design
OpenSearch
Vector stores

Job description

Huron is seeking an experienced Director-level AI Security professional in the United States to translate security, privacy, and architecture requirements into executable platform controls for AI workloads. You will define classification patterns, control sets, and audit evidence across the AI lifecycle, partnering with infrastructure teams to implement automated reporting and telemetry.

Join a role focused on governance engineering, evaluation patterns, and knowledge management for MVP

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