Jobs / United States / Humana INC
Associate Vice President, Model & AI Governance
Humana INC · 🇺🇸 Remote Nationwide · Remote
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 260 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 130 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Humana INC paid sponsored hires in similar roles3 certified filings for “Associate Director, Technology Solutions” (Computer and Information Systems Managers) in KY: $154k–$179k, median $162k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Humana INC
The US Department of Labor certified 260 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 130 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Humana INC →
About the role
Become a part of our caring community The Associate Vice President, Model & AI Governance, is the enterprise leader responsible for establishing and overseeing the organization’s framework for model governance, artificial intelligence (AI) risk management, responsible AI and AI governance. Reporting to the Chief Audit & Risk Officer, this executive provides independent second-line oversight and challenge of the organization’s use of models, advanced analytics, machine learning, generative AI, and emerging AI technologies. The role establishes the governance, risk-management, control, monitoring and escalation framework necessary to ensure AI models are deployed in a manner that is safe, ethical, transparent, explainable, compliant, secure and aligned with the organization’s mission and risk appetite. The Associate Vice President, Model & AI Governance, partners closely with executive leadership, technology, data and analytics, clinical/business leaders, compliance, legal, privacy, cybersecurity, information security, internal audit, enterprise risk management and other control functions to ensure AI-related risks are identified, assessed, governed, monitored, and appropriately reported. This leader will serve as an advisor to executive management on emerging model and AI risks, while maintaining appropriate independence from the teams developing and deploying models and AI solutions. Key Responsibilities • Own and continuously enhance the enterprise model governance framework, including model identification, inventory, classification, risk tiering, development, validation, approval, implementation, monitoring, change management, retirement and documentation. • Define model risk appetite, risk taxonomy, minimum control standards, governance requirements and escalation thresholds. • Provide effective challenge over model development, validation, implementation, monitoring and performance. • Oversee the enterprise model inventory and ensure appropriate ownership, accountability, documentation, and risk classification. • Establish standards for model validation, including conceptual soundness, performance, stability, data quality, bias, explainability and ongoing monitoring. • Ensure appropriate governance over third-party and externally developed models. • Develop and oversee the organization’s Responsible AI framework and principles. • Establish governance standards addressing fairness, bias, transparency, explainability, accountability, privacy, human oversight, safety, security, and appropriate use of AI. • Establish processes for AI use-case risk intake, risk assessment, approval, monitoring, and ongoing oversight, working closely with other AI governance functions to simplify and streamline processes. • Develop standards for responsible use of generative AI, large language models, AI agents, automated decision-making and other emerging technologies, partnering with other stakeholders to ensure cross functional alignment • Establish governance mechanisms to identify and address unintended consequences, model drift, hallucination, discrimination, explainability limitations, and other AI-specific risks. • Own the enterprise AI risk management framework and associated governance processes. • Establish governance requirements and oversight for the enterprise AI inventory, ensuring AI applications and use cases are appropriately inventoried, classified, risk-rated, assigned accountable ownership, and monitored throughout their lifecycle. • Develop AI risk assessments and approval requirements proportionate to the potential impact of technology. • Establish ongoing monitoring of AI performance, effectiveness, risk indicators, incidents, exceptions and emerging threats. • Partner with cybersecurity, Privacy, Legal,