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Director Model Risk Governance Jobs in Leland, NC

Luxoft

AI Governance & Controls Lead

Wilmington, NC · On-site

Project description The AI Governance & Controls Lead is the senior individual contributor ... This role partners closely with Technology Risk Management, Model Risk Management, Compliance ...

New

Luxoft

GenAI Solutions Architect

Wilmington, NC · On-site

$53.50 - $70.50/hr

Partner with Cybersecurity architecture on AI threat modeling, prompt-injection risk, and ... Support solution reviews in governance forums with clear, evidence-based architecture assessments.

Luxoft

GenAI Platform Engineering Team Lead

Wilmington, NC · On-site

$86K - $114K/yr

Represent platform status, risks, and trade-offs to the Director and governance forums with ... Hands-on GenAI experience: model integration, RAG patterns, and AI-assisted engineering workflows.

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Director Model Risk Governance information

See Leland, NC salary details

$46.7K

$123.8K

$224.7K

How much do director model risk governance jobs pay per year?

As of Aug 17, 2026, the average yearly pay for director model risk governance in Leland, NC is $123,762.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,200.00 and $144,800.00 per year, depending on experience, location, and employer.

What is the difference between Director Model Risk Governance vs Model Risk Analyst?

AspectDirector Model Risk GovernanceModel Risk Analyst
CredentialsAdvanced degrees (e.g., Master’s, PhD), professional certifications (e.g., FRM, CFA)Bachelor’s or Master’s degree, relevant certifications
Work EnvironmentStrategic oversight, policy development, senior stakeholder engagementData analysis, model validation, risk assessment
Employer & Industry UsageFinancial institutions, banks, asset managersFinancial institutions, risk management teams
Search & Comparison IntentUnderstanding leadership roles in model risk governanceEntry to mid-level model risk roles, analysis tasks

The main difference is that the Director Model Risk Governance focuses on strategic oversight, policy setting, and managing model risk at a senior level, while the Model Risk Analyst handles technical validation, data analysis, and risk assessment tasks. The director role involves leadership and decision-making, whereas the analyst role is more technical and operational.

What are the key skills and qualifications needed to thrive as a director model risk governance?

To thrive as a Director of Model Risk Governance, you need deep expertise in quantitative finance, risk management, and model validation, often backed by an advanced degree in a quantitative field and relevant industry experience. Familiarity with risk management frameworks, regulatory standards (e.g., SR 11-7), and proficiency in analytical tools like Python, R, or SAS are typically required. Exceptional leadership, communication, and critical thinking skills help you effectively oversee teams and coordinate with stakeholders across the organization. These competencies are vital to ensure robust model governance, regulatory compliance, and informed risk-based decision-making at the enterprise level.

What is a director model risk governance?

Director Model Risk Governance roles are senior positions responsible for overseeing and managing the risks associated with financial and predictive models within an organization. These professionals establish and implement model risk management frameworks, ensure compliance with regulatory requirements, and oversee model validation processes. They collaborate with model developers, validators, and business units to identify, assess, and mitigate model risks, as well as report on governance effectiveness to senior management. Their work is crucial in maintaining the reliability and integrity of models used for decision-making and regulatory reporting.

What are some common challenges faced by a director model risk governance, and how can they be addressed?

A Director of Model Risk Governance often encounters challenges such as ensuring consistent model validation across diverse business units, keeping up with evolving regulatory requirements, and fostering effective communication between model owners, validators, and senior management. Addressing these challenges typically involves establishing robust model risk frameworks, maintaining clear documentation, and promoting a culture of transparency and collaboration. Regular training sessions and open forums can help bridge knowledge gaps, while leveraging technology can streamline model inventory and validation processes.

What are popular job titles related to Director Model Risk Governance jobs in Leland, NC?

For Director Model Risk Governance jobs in Leland, NC, the most frequently searched job titles are:

What cities near Leland, NC are hiring for Director Model Risk Governance jobs?

Cities near Leland, NC with the most Director Model Risk Governance job openings:

Director Model Risk Governance jobs near you

AI Governance & Controls Lead

Luxoft

Wilmington, NC • On-site

Other

Posted 3 days ago

New

Job description

Project description
The AI Governance & Controls Lead is the senior individual contributor responsible for operationalizing client's AI governance framework: authoring and maintaining AI standards and controls, executing the policy exception and deviation processes, and producing the examiner-ready evidence that demonstrates our controls are enforced mechanically rather than attested annually. This role partners closely with Technology Risk Management, Model Risk Management, Compliance, Cybersecurity, Enterprise Architecture, and the enterprise AI platform team to ensure every AI use case at the bank operates within a defensible, testable control framework.
This is a hands-on, technically fluent governance role. The Lead works directly with platform-enforced controls (gateway policies, entitlements, quotas, audit logging), translates regulatory obligations (e.g., SR 26-2, NYDFS guidance) into implementable standards, and validates that evidence generated by the platform satisfies second-line and examiner expectations. The role serves as a key contributor to policy refresh cycles, regulatory response efforts, and the continuous-monitoring design that replaces point-in-time annual review
Responsibilities
Standards, Controls & Policy Execution
Author, maintain, and version the bank's AI standards library: model selection and approval, human oversight tiers, prompt/response logging and retention, agentic guardrails, and acceptable-use requirements.
Build and maintain the obligation-to-control-to-evidence mapping against applicable regulatory guidance (SR 26-2, NYDFS, and evolving supervisory expectations).
Operate the AI policy exception and TRM deviation processes: draft time-bound deviation requests, define compensating controls, track expiries and remediation paths to closure.
Support annual policy refresh cycles and translate policy principles into testable, enforceable requirements in partnership with policy owners.
Platform-Enforced Governance & Evidence
Partner with the AI platform team to ensure governance requirements are enforced mechanically at the enterprise AI gateway (entitlements, model allowlists, quotas, audit logging) and that enforcement produces native evidence.
Define evidence requirements and validate audit artifacts as queryable, export-ready, and sufficient for internal audit, second-line review, and examiner requests.
Design and operate continuous-monitoring practices: monitoring boundaries, event-based review triggers, and evidence expectations for AI systems that change frequently.
Maintain the AI use case and agent registry as the system of record, integrated with platform onboarding and entitlement workflows.
Provide governance ownership of the AI use-case intake framework in partnership with the AI Use Case Intake & Value Lead.
Risk Partnership & Regulatory Readiness
Serve as the primary working-level interface to Technology Risk Management, Model Risk Management, Compliance, and Internal Audit for AI governance matters.
Assemble examiner-readiness packages: control mappings, evidence samples from the live platform, and documented rationale for the standards the bank has defined.
Monitor the regulatory and industry landscape (agency guidance, FSB/trade-group developments) and assess impact to standards and controls.
Support AI Control Group and AI Ethics Working Group activities with documented assessments and control recommendations.
Skills
Must have
Bachelor's degree and a minimum of 5 years' experience in technology risk, IT governance, information security governance, or technology compliance within a regulated environment, or in lieu of a degree, a combined minimum of 9 years' education and/or relevant work experience.
Demonstrated experience authoring technology standards, controls, or policies and mapping them to regulatory obligations.
Working technical fluency with modern AI systems: LLM-based applications, API gateways, model access patterns, RBAC/entitlements, logging and monitoring architectures.
Experience preparing for or responding to internal audit, second-line review, or regulatory examination.
Strong analytical writing: able to produce standards, deviation requests, and evidence narratives that survive challenge.
Strong communication and stakeholder management skills across risk, technology, and business partners
Nice to have
Experience with AI/ML governance frameworks (NIST AI RMF, model risk management guidance, SR 11-7/SR 26-2 lineage).
Familiarity with Azure services relevant to AI workloads (API Management, Entra ID, Key Vault, Azure Monitor) and with policy-as-code or controls-automation concepts.
Financial services or other highly regulated industry experience.
Experience with GRC tooling and evidence management.
Experience supporting AI, data, or technology committees and governance forums
Other
Languages
English: C1 Advanced
Seniority
Lead

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