Director, AI Governance & Security Architecture

Huron; Chicago (IL); On-site; USD 190,000 - 265,000; Full time

Benefits offered by this job

Medical coverage

Dental and vision coverage

Wellness programs

Job summary

Huron, a global consultancy, seeks an AI Security, Governance, Engineering and Observability expert to translate security, privacy, compliance, and architecture requirements into executable platform controls. You will establish patterns for telemetry, dashboards, and audit evidence while driving MVP validation for Huron Knowledge capabilities.

Jointly with infrastructure teams, you will design retrieval quality metrics, model evaluation patterns, and governance controls for AI workloads,

Qualifications

• 8+ years of experience across cloud security, platform security, governance engineering, security architecture, data engineering, observability, analytics engineering, ML evaluation, or AI application monitoring.
• Strong understanding of identity, network controls, secrets management, logging, audit trails, data classification, least-privilege design, and evidence capture.
• Familiarity with retrieval-augmented generation, embeddings, vector stores, metadata, indexing, citation, access control, and knowledge-source quality.
• Ability to translate policy, risk, quality, and observability requirements into practical engineering controls and metrics.
• Strong software, data engineering, automation, or analytics engineering skills.
• Demonstrated ability to use AI tools as a practical system-building accelerator for governance engineering, analysis, dashboard development, evaluation, documentation, or control review.
• Strong documentation and communication skills for control standards, decision records, dashboards, exception patterns, and audit evidence.

Responsibilities

• Translate security, privacy, compliance, and architecture requirements into executable controls for AI workloads.
• Define workload classification patterns and required controls for each class.
• Establish prompt, response, embedding, retrieval, logging, retention, redaction, and client data segregation patterns in partnership with control functions.
• Define audit evidence patterns for model access, data movement, retrieval, tool calls, approvals, exceptions, and operational events.
• Design identity, secrets, network, sandbox, logging, and approval-gate patterns for AI applications and agents.
• Build governed knowledge patterns for authoritative sources, ingestion, indexing, metadata, access control, freshness, citation, and retrieval evaluation.
• Help select the first Huron Knowledge domain, source, or integration pattern for MVP validation.
• Define and implement retrieval quality metrics, model evaluation patterns, regression checks, operational telemetry, dashboards, and quality reporting.
• Partner with infrastructure engineers to implement controls, evidence, and reporting through automation rather than manual processes.
• Help teams understand whether AI systems are producing useful, grounded, safe, auditable, and cost-effective outputs.
• Use AI tools hands-on to accelerate control design, policy mapping, knowledge analysis, evaluation design, dashboard development, documentation, and evidence review.

Skills

Cloud security

Governance engineering

Security architecture

ML evaluation

AI governance

Tools

AWS

OpenSearch

BI tools

Job description

Huron, a global consultancy, seeks an AI Security, Governance, Engineering and Observability expert to translate security, privacy, compliance, and architecture requirements into executable platform controls. You will establish patterns for telemetry, dashboards, and audit evidence while driving MVP validation for Huron Knowledge capabilities.

Jointly with infrastructure teams, you will design retrieval quality metrics, model evaluation patterns, and governance controls for AI workloads,