Principal AI Governance Architect

Huron

Principal AI Governance Architect securing and governing AI workloads for Huron, a global consultancy. Building controls, knowledge systems, evaluations, telemetry, dashboards, and audit evidence.

Posted 8/4/2026full-timeRemote • 🇺🇸 United StatesLead💰 $190,000 - $265,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in translating security, privacy, and compliance requirements into actionable controls for AI workloads, with a strong focus on governance engineering and data protection. Proficient in using AI tools for evaluation, documentation, and dashboard development to ensure quality and compliance in AI systems.

Highest-signal resume keywords

Cloud SecurityGovernance EngineeringAI Tools UtilizationData EngineeringModel Risk Management

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Security ArchitectureData ClassificationAudit TrailsAutomationML EvaluationRetrieval-Augmented GenerationEmbeddingVector StoresRegression TestingQuality Reporting

Soft Skills

Documentation SkillsCommunication Skills

Tools & Technologies

Amazon BedrockAWS IAMCloudTrailCloudWatchOpenSearchBI ToolsTemporalVPC DesignKMSObservability Platforms

Industry Keywords

AI GovernanceData ProtectionSensitive Data EnvironmentsClient ConfidentialRegulated Environments

Tech Stack

Tools & technologies

AWSCloud

About the role

Key responsibilities & impact

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
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 covering authoritative sources, ingestion, indexing, metadata, access control, freshness, citation, and retrieval evaluation
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
Assess whether AI systems produce useful, grounded, safe, auditable, and cost-effective outputs
Use AI tools to accelerate control design, policy mapping, knowledge analysis, evaluation design, dashboard development, documentation, and evidence review

Requirements

What you’ll need

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 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
Experience with AI governance, model risk management, LLM application security, agent security, or data protection for AI systems preferred
Experience with Amazon Bedrock, AWS IAM, CloudTrail, CloudWatch, PrivateLink, KMS, VPC design, OpenSearch, vector databases, BI tools, or observability platforms preferred
Experience with LLM evaluation, prompt evaluation, retrieval evaluation, golden datasets, regression testing, or AI quality frameworks preferred
Experience with Temporal or comparable workflow orchestration platforms preferred
Experience with enterprise knowledge systems, document repositories, metadata governance, search relevance, or permission-aware retrieval preferred
Experience with PHI, PII, client-confidential, regulated, or sensitive-data environments preferred
Flexible living locations across the US
Ability to travel as needed

Benefits

Comp & perks

Annual incentive compensation program
Medical, dental, and vision coverage for employees and dependents
Other wellness programs
401(k) plan with a generous employer match
Employee stock purchase plan
Generous Paid Time Off policy
Paid parental leave
Adoption assistance
Free annual health screenings and coaching
Bank at work
On-site workshops
Ongoing programs recognizing major events in employees’ lives