Location Designation: Hybrid - 3 days per week 

Business Unit

Technology, Data, AI and Ventures (TDAV)

Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life's businesses. We build solutions that power how we serve policy owners, agents, advisors and employees while delivering measurable business outcomes.

Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader, access to leading-edge technologies and the opportunity to help shape how a world-class financial services company competes in the AI era — all backed by the stability and purpose of a mutual company built to last.

Role Overview

The Corporate Vice President – Model Validation and AI Governance will play a key leadership role in strengthening New York Life’s approach to model validation and responsible AI governance across predictive, generative, and agentic AI solutions. Working closely with Model Risk Management and partners across Artificial Intelligence & Data, Technology, Risk, Legal, Compliance, Cybersecurity, and Third-Party Risk Management, this role will translate model risk requirements into rigorous, practical validation approaches and controls.

This role will lead complex validation engagements end-to-end for internally developed and third-party solutions, independently challenging model methodologies, evaluation approaches, controls, and monitoring strategies. A particular focus will be establishing robust approaches for evaluating agentic and multi-step AI systems, including tool use, orchestration, autonomy, guardrails, human oversight, observability, and emerging failure modes.

The successful candidate will combine deep quantitative and AI expertise with strong risk judgment and communication skills. They will establish validation standards and reusable practices, mentor junior colleagues, and communicate technical findings, limitations, and conditions of use in clear terms that enable senior stakeholders and governance forums to make informed decisions.

What You'll Do

• Lead independent validation and effective challenge across predictive, machine learning, generative AI, and agentic AI solutions, assessing model design, data and feature pipelines, methodologies, evaluation metrics, assumptions, limitations, and business impact. For agentic systems, evaluate architecture, planning and orchestration, tool use and permissions, retrieval and prompt design, memory and state, autonomy boundaries, guardrails, human-in-the-loop controls, and escalation and fallback mechanisms.

• Design and advance rigorous AI evaluation practices by developing and challenging evaluation frameworks, benchmark and golden datasets, rubric-based and LLM-as-a-judge scoring, human review protocols, regression suites, offline and online testing, and adversarial or red-team evaluations. Assess statistical rigor, coverage, reproducibility, and the strength of validation evidence for high-impact use cases.

• Establish monitoring, observability, and third-party validation approaches that address model drift, bias and fairness, stability, hallucinations, business outcomes, and agentic failure modes. Evaluate vendor and foundation-model solutions through independent testing and due diligence, and partner with teams to establish tracing, logging, telemetry, dashboards, alerts, compensating controls, and audit-ready evidence.

• Translate risk and regulatory expectations into practical controls by interpreting technical standards, regulatory guidance, and internal procedures and converting requirements into validation methodologies, checklists, playbooks, standard operating procedures, monitoring expectations, and evidence requirements. Present validation findings, limitations, and conditions of use to senior stakeholders and governance committees.

• Set standards and strengthen validation capabilities across teams by developing reusable templates, guidelines, test harnesses, and best practices for predictive, generative, and agentic AI; mentoring and reviewing the work of junior colleagues; partnering across data science, engineering, product, and control functions; and remaining current on evolving modeling techniques, AI research, evaluation methodologies, observability technologies, and governance practices.

What You'll Bring

Required Skills

• Advanced degree in Statistics, Computer Science, Data Science, Mathematics, Economics, Engineering, or a related quantitative discipline, with strong knowledge of statistics and 7+ years of experience in model validation, model governance, or model risk management for predictive and AI/ML solutions within regulated environments.

• Deep hands-on knowledge of traditional statistical and machine learning approaches, combined with demonstrated experience validating generative and agentic AI systems, including multi-step workflows, tool use, orchestration and planning, guardrails, autonomy controls, human oversight, and agent-specific failure modes.

• Demonstrated experience designing, building, or independently reviewing AI evaluation frameworks, including dataset curation, benchmark design, rubric-based and LLM-as-a-judge evaluation, human review, regression testing, retrieval-quality assessment, and adversarial or red-team testing.

• Practical experience with AI/ML monitoring and observability, including tracing, logging, telemetry, dashboards, and alerting, as well as experience validating or overseeing third-party, vendor-hosted, foundation-model, or other limited-transparency AI solutions.

• Proficiency in Python and SQL, with experience using agent orchestration, evaluation, observability, or related AI tooling and the technical depth to independently replicate results, conduct diagnostic analysis, and build challenger approaches when appropriate.

• Strong communication, leadership, and analytical skills, including the ability to interpret technical and regulatory requirements, translate them into practical controls, lead complex validations end-to-end, mentor colleagues, and present and defend technical findings with senior leaders and cross-functional governance bodies.

Preferred Skills

• Experience evaluating Generative AI solutions, including prompting strategies, retrieval-augmented generation (RAG), retrieval quality, model adaptation or fine-tuning trade-offs, and AI-specific privacy, security, interpretability, and stress-testing considerations.

• Knowledge of agentic AI risks and controls, including prompt injection, excessive agency, tool and permission scoping, action reversibility, guardrail effectiveness, and hands-on exposure to commercial or open-source AI evaluation, observability, or guardrail technologies.

• Familiarity with model and AI risk frameworks and emerging regulatory expectations, including SR 11-7, the NIST AI Risk Management Framework, the NAIC Model Bulletin on AI, and the EU AI Act, as well as experience collaborating with Legal, Compliance, Cybersecurity, and Third-Party Risk Management functions.

• Applied understanding of AI use cases within financial services or insurance, such as underwriting support, fraud detection, marketing and sales enablement, agent productivity, and customer service, including the strengths, limitations, and evolving failure modes associated with generative and agentic AI.

Pay Transparency

Salary Range: $147,500-$211,000 

Overtime eligible: Exempt 

Discretionary bonus eligible: Yes 

Sales bonus eligible: No 

Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.

Our Benefits

We provide a full package of benefits for employees – and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work. Click here to discover more about our comprehensive benefit options or visit our NYL Benefits Site.

Our Commitment to Inclusion
At New York Life, fostering an inclusive workplace is fundamental to who we are and how we serve our communities. We have a longstanding commitment to creating an environment where individuals can contribute their best and succeed together. This foundation is rooted in our core values of humanity and integrity, ensuring that every employee feels valued and supported. By embracing a broad range of perspectives and experiences, we achieve greater success and fulfill our promise of providing financial security and peace of mind to families across all communities. Click here to learn more about New York Life’s leadership in this space.​

Recognized as one of Fortune’s World’s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com.

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Job Requisition ID: 94710