AI Governance and Controls Architect

HealthEquity•Remote,

1d•$127,000 - $165,000•Remote

About The Position

HealthEquity is expanding the use of Artificial Intelligence (AI), including generative and agentic, to improve member, client, and teammate experiences while maintaining trust, safety, and compliance. The Principal Responsible AI Governance and Compliance role is a senior technical governance role responsible for ensuring AI systems are designed, deployed, and operated in a manner that is secure, compliant, auditable, and aligned with HealthEquity’s Responsible AI principles. In this role, you will translate Responsible AI policy and governance requirements into concrete technical controls, validation mechanisms, and continuous‑assurance practices that scale across internal and third‑party AI systems. Partnering with IT, Engineering, Product Development, Legal, Privacy, and internal Security teams, you will directly influence how AI is built and governed by embedding risk‑based guardrails, evaluation standards, and monitoring into engineering and platform workflows—enabling innovation while reducing regulatory, security, privacy, and operational risk. This role is critical to making AI governance real, defensible, and operational, ensuring HealthEquity can confidently adopt advanced AI capabilities without compromising member trust or regulatory obligations.

Requirements

Strong understanding of AI/ML and GenAI systems, including LLMs, RAG architectures, agentic workflows, tool‑calling patterns, and human‑oversight mechanisms.
Hands‑on experience with AI risk assessment and validation, including bias/fairness, robustness, hallucinations, drift, security threats, and misuse scenarios.
Experience translating governance or regulatory expectations into engineering‑ready controls, quality gates, and acceptance criteria.
Familiarity with AI governance and risk frameworks (e.g., NIST AI RMF, NIST CSF, SOC 2 principles) and applying them pragmatically to real systems.
Comfort using tooling and automation (e.g., dashboards, evidence repositories, scripting, APIs, workflow tools) to reduce manual governance overhead.
Bachelor’s degree in Computer Science, Engineering, Data Science, Information Security, or a related field (or equivalent practical experience).
3+ years of direct experience working with or governing AI/ML systems in production or near‑production environments.
Experience supporting audit, regulatory, or client assurance efforts through high‑quality technical documentation and evidence.
Ability to clearly communicate complex technical risk and control concepts to engineering, security, privacy, legal, and executive stakeholders.
Strong technical writing skills for model documentation, validation summaries, decision logs, and audit responses.
Sound judgment in balancing risk rigor with engineering practicality in fast‑moving AI development environments.
Proven ability to influence without authority and act as a trusted technical advisor in governance decisions.

Responsibilities

Engineer and operationalize technical AI governance controls across the full AI lifecycle, translating Responsible AI requirements into testable, measurable, and auditable controls.
Lead or support technical assurance reviews for AI use cases, validating that documented behaviors, risks, and mitigations align with observed system behavior.
Design and standardize AI governance artifacts, such as model/system cards, evaluation summaries, architecture and data‑flow documentation, risk‑and‑control mappings, and approval evidence.
Establish continuous assurance mechanisms for AI systems by defining monitoring signals, metrics, dashboards, and automated evidence collection.
Partner with security, privacy, data governance, legal, product, and engineering teams to embed AI controls by design into development and platform workflows.
Drive continuous improvement efforts by identifying opportunities for enhancing security governance, risk management, and compliance practices.
Serve as a principal technical subject matter expert on end-to-end AI governance lifecycle, providing guidance and advice to senior management on best practices and emerging
Other AI Gov activities assigned by leadership.