More jobs:
Principal AI Governance Architect
Job in
Chicago, Cook County, Illinois, 60290, USA
Listed on 2026-08-08
Listing for:
Huron Consulting Group Inc.
Full Time
position Listed on 2026-08-08
Job specializations:
-
IT/Tech
AI Evaluation, Cybersecurity, Information & Knowledge Management, Information Security & Data Protection
Job Description & How to Apply Below
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.
AI Security, Governance, Engineering and Observability roleThe 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.
- 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.
- Experience with AI governance, model risk management, LLM application security, agent security, or data protection for AI systems.
- Experience with Amazon Bedrock, AWS IAM, Cloud Trail, Cloud Watch, Private Link, KMS, VPC design, Open Search, 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.
- Ab…
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
Search for further Jobs Here:
×