Huron

Principal AI Governance Architect

United States · Remote (restrictions not stated) · Full time

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About the role

Description from the employer’s posting. Check the employer’s page for the current version.

EmployerHuron
LocationUnited States
Work styleRemote (restrictions not stated)
Employment typeFull time
Employer posted4 Aug 2026

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future.

Join our team as the expert you are now and create your future.

The AI Security, Governance, Engineering and Observability role will translate security, privacy, compliance, architecture, and business requirements into executable platform controls while also establishing the first patterns for Huron Knowledge enablement, evaluation, telemetry, dashboards, audit evidence, and operational reporting.

Key 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.

Show full description

Required 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.

Preferred Qualifications

Experience with AI governance, model risk management, LLM application security, agent security, or data protection for AI systems.
Experience with Amazon Bedrock, AWS IAM, CloudTrail, CloudWatch, PrivateLink, KMS, VPC design, OpenSearch, vector databases, BI tools, or observability platforms.
Experience with LLM evaluation, prompt evaluation, retrieval evaluation, golden datasets, regression testing, or AI quality frameworks.
Experience with Temporal or comparable workflow orchestration platforms for approval flows, evidence capture, evaluation workflows, or operational reporting.
Experience with enterprise knowledge systems, document repositories, metadata governance, search relevance, or permission-aware retrieval.
Experience with PHI, PII, client-confidential, regulated, or sensitive-data environments.

Flexible living locations across the US. Ability to travel as needed.

The estimated base salary for this job is $190,000 - $265,000 USD. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $237,000 - $357,000 USD. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.

Position Level

Director

Country

United States of America

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