VP Of AI Jobs
VP Of AI jobs are open across technology, financial services, healthcare, and retail, from director-level first-timers to seasoned C-suite executives, with specializations in generative AI strategy, AI product development, and enterprise machine learning. Find a role that fits from the openings below and apply directly.
Find VP Of AI JobsOverview
Showing 5 of 66+ VP Of AI jobs
Job Description
Requisition ID
Department
Job Function
Location
Role Location Designation
Location Designation: Hybrid - 3 days per week
Role Overview
We are building a small, senior AI engineering team responsible for creating New York Life's enterprise AI platform—and the first generation of agentic AI solutions that run on it.
This team sits at the intersection of AI platform engineering, agentic system design, cloud architecture, and enterprise governance. Our mission is to build secure, governable, production-ready AI capabilities on top of enterprise data, APIs, and cloud-native platform services, moving beyond pilots to scalable business outcomes.
As AI Platform Lead, you will define how agentic AI is architected, deployed, secured, evaluated, and scaled responsibly across the enterprise. You will lead the team building the company's AI backbone—the governed platform that powers enterprise AI applications and enables the first wave of agentic insurance solutions. This is a rare opportunity to shape a greenfield platform with executive sponsorship, modern cloud technologies, and a small, highly experienced engineering team.
This is a hands-on player-coach role for an engineering leader who enjoys deep technical ownership across the full technology stack—from cloud infrastructure and runtime architecture to tool orchestration, retrieval, memory, evaluation, and agent behavior. You will establish the technical vision, mentor senior engineers, and remain actively involved in architecture, coding, and solution delivery.
The platform is built on Google Cloud and designed to leverage cloud-native capabilities while maintaining portability through open architectures and reusable engineering patterns. Success in this role requires balancing innovation with governance, enabling responsible AI adoption in a highly regulated enterprise while delivering measurable business value.
Our Engineering Principles
Our team is intentionally small, senior, and highly technical. Regardless of title, every engineer is expected to build AI systems—and build with AI.
• Build agents that power the platform. Develop platform capabilities as intelligent agents—not just traditional services. Examples include lifecycle management agents that register, version, monitor, govern, and retire AI assets across the enterprise.
• Build cloud agents that plan and implement. Create agents that can translate business needs into implementation plans, orchestrate the required skills and tooling, and execute work with human oversight at the appropriate checkpoints.
• Build end-to-end multi-agent solutions. Design and implement solutions where specialized agents collaborate to architect systems, provision infrastructure, generate code, validate through dedicated testing agents, deploy applications, perform post-deployment verification, and maintain complete operational traceability.
• Build with AI-assisted engineering tools. Be fluent with modern AI development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, or equivalent technologies. AI-assisted software development is a core engineering competency and will be evaluated throughout the interview process.
What You'll Do:
• Define the technical vision and reference architecture across the enterprise AI platform, including agent lifecycle services, orchestration capabilities, retrieval and memory services, and AI control plane components that integrate with enterprise AI services.
• Own and execute the multi-phase platform roadmap, delivering foundational AI platform capabilities, reusable platform services, enterprise knowledge capabilities, and end-to-end builder agents that accelerate AI solution delivery.
• Lead, mentor, and develop a high-performing team of senior AI engineers while maintaining hands-on ownership of architecture, engineering, and agent development. Establish a high engineering bar and champion AI-assisted software development practices.
• Partner with Security, Risk, Legal, and enterprise stakeholders to operationalize AI governance, automate solution review processes, and ensure alignment with enterprise AI risk management standards and responsible AI practices.
• Drive cloud architecture decisions, build-versus-buy evaluations, and platform portability strategies while leveraging Google Cloud capabilities without creating unnecessary vendor lock-in.
• Establish AI FinOps capabilities, including model usage visibility, infrastructure cost attribution, dashboards, and budget guardrails that enable responsible scaling across the enterprise.
• Partner with business and technology leaders to deliver the first generation of enterprise agentic AI solutions that demonstrate measurable business outcomes.
• Build agents that improve the platform itself while leveraging AI-assisted engineering throughout the software development lifecycle.
What You'll Bring:
Required Skills
• Proven experience leading the delivery of enterprise AI platforms, ML platforms, developer platforms, or cloud-native engineering platforms operating at production scale.
• Deep expertise with cloud architecture and modern infrastructure, including Google Cloud Platform (preferred), Kubernetes, containers, Infrastructure as Code (Terraform), CI/CD, networking, identity, and observability.
• Strong experience designing and building production-grade generative AI and agentic systems, including LLMs, retrieval-augmented generation (RAG), memory architectures, multi-agent orchestration, tool integration, Model Context Protocol (MCP), agent-to-agent (A2A) communication, and evaluation frameworks.
• Experience implementing AI governance, security, and responsible AI practices within regulated industries, including AI risk management, runtime guardrails, model controls, privacy, and compliance considerations.
• Demonstrated ability to lead senior engineering teams, establish technical direction, influence executive stakeholders, and successfully deliver complex technical roadmaps.
• Strong software engineering background with production experience in Python and modern software architecture.
• Experience using AI-assisted software development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, or similar technologies to accelerate engineering productivity.
• Excellent communication and collaboration skills with the ability to influence both technical and business stakeholders.
Preferred Skills
• Experience building enterprise AI platforms within financial services, insurance, or another highly regulated industry.
• Experience with Vertex AI, LangChain, Google ADK, AutoGen, CrewAI, OpenTelemetry, and modern AI platform technologies.
• Knowledge of enterprise AI governance frameworks including NIST AI RMF, ISO 42001, SOC 2, HIPAA, GDPR, or emerging AI regulations.
• Experience leading greenfield platform initiatives and building high-performing engineering organizations.
Why This Role
• Build the foundation. Define the architecture, standards, and operating model for enterprise AI across New York Life.
• Lead a senior team. Join a small, highly experienced engineering organization where technical excellence, ownership, and collaboration are the norm.
• Work on frontier technology. Build production-scale agentic AI systems and AI platforms that solve meaningful business problems in a highly regulated environment.
• Create enterprise impact. Shape how AI is responsibly adopted across the company and deliver capabilities that will enable teams across the enterprise for years to come.
• Stay hands-on. Continue building, architecting, and shipping while leading a team of exceptional engineers.
Location
We are committed to attracting exceptional talent and will consider flexible work arrangements for the right candidate.
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.
Company Overview
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.
Our diverse business portfolio creates opportunities to make a difference across industries and communities—inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you’ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what’s next, and your growth powers it.
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.
Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.
Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees’ needs.
Job Requisition ID: 94418
Read More
Job Description
Requisition ID
Department
Job Function
Location
Role Location Designation
Location Designation: Hybrid - 3 days per week
Role Overview
We are building a small, senior AI engineering team responsible for creating New York Life's enterprise AI platform—and the first generation of agentic AI solutions that run on it.
This team sits at the intersection of AI platform engineering, agentic system design, cloud architecture, and enterprise governance. Our mission is to build secure, governable, production-ready AI capabilities on top of enterprise data, APIs, and cloud-native platform services, moving beyond pilots to scalable business outcomes.
As AI Platform Lead, you will define how agentic AI is architected, deployed, secured, evaluated, and scaled responsibly across the enterprise. You will lead the team building the company's AI backbone—the governed platform that powers enterprise AI applications and enables the first wave of agentic insurance solutions. This is a rare opportunity to shape a greenfield platform with executive sponsorship, modern cloud technologies, and a small, highly experienced engineering team.
This is a hands-on player-coach role for an engineering leader who enjoys deep technical ownership across the full technology stack—from cloud infrastructure and runtime architecture to tool orchestration, retrieval, memory, evaluation, and agent behavior. You will establish the technical vision, mentor senior engineers, and remain actively involved in architecture, coding, and solution delivery.
The platform is built on Google Cloud and designed to leverage cloud-native capabilities while maintaining portability through open architectures and reusable engineering patterns. Success in this role requires balancing innovation with governance, enabling responsible AI adoption in a highly regulated enterprise while delivering measurable business value.
Our Engineering Principles
Our team is intentionally small, senior, and highly technical. Regardless of title, every engineer is expected to build AI systems—and build with AI.
• Build agents that power the platform. Develop platform capabilities as intelligent agents—not just traditional services. Examples include lifecycle management agents that register, version, monitor, govern, and retire AI assets across the enterprise.
• Build cloud agents that plan and implement. Create agents that can translate business needs into implementation plans, orchestrate the required skills and tooling, and execute work with human oversight at the appropriate checkpoints.
• Build end-to-end multi-agent solutions. Design and implement solutions where specialized agents collaborate to architect systems, provision infrastructure, generate code, validate through dedicated testing agents, deploy applications, perform post-deployment verification, and maintain complete operational traceability.
• Build with AI-assisted engineering tools. Be fluent with modern AI development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, or equivalent technologies. AI-assisted software development is a core engineering competency and will be evaluated throughout the interview process.
What You'll Do:
• Define the technical vision and reference architecture across the enterprise AI platform, including agent lifecycle services, orchestration capabilities, retrieval and memory services, and AI control plane components that integrate with enterprise AI services.
• Own and execute the multi-phase platform roadmap, delivering foundational AI platform capabilities, reusable platform services, enterprise knowledge capabilities, and end-to-end builder agents that accelerate AI solution delivery.
• Lead, mentor, and develop a high-performing team of senior AI engineers while maintaining hands-on ownership of architecture, engineering, and agent development. Establish a high engineering bar and champion AI-assisted software development practices.
• Partner with Security, Risk, Legal, and enterprise stakeholders to operationalize AI governance, automate solution review processes, and ensure alignment with enterprise AI risk management standards and responsible AI practices.
• Drive cloud architecture decisions, build-versus-buy evaluations, and platform portability strategies while leveraging Google Cloud capabilities without creating unnecessary vendor lock-in.
• Establish AI FinOps capabilities, including model usage visibility, infrastructure cost attribution, dashboards, and budget guardrails that enable responsible scaling across the enterprise.
• Partner with business and technology leaders to deliver the first generation of enterprise agentic AI solutions that demonstrate measurable business outcomes.
• Build agents that improve the platform itself while leveraging AI-assisted engineering throughout the software development lifecycle.
What You'll Bring:
Required Skills
• Proven experience leading the delivery of enterprise AI platforms, ML platforms, developer platforms, or cloud-native engineering platforms operating at production scale.
• Deep expertise with cloud architecture and modern infrastructure, including Google Cloud Platform (preferred), Kubernetes, containers, Infrastructure as Code (Terraform), CI/CD, networking, identity, and observability.
• Strong experience designing and building production-grade generative AI and agentic systems, including LLMs, retrieval-augmented generation (RAG), memory architectures, multi-agent orchestration, tool integration, Model Context Protocol (MCP), agent-to-agent (A2A) communication, and evaluation frameworks.
• Experience implementing AI governance, security, and responsible AI practices within regulated industries, including AI risk management, runtime guardrails, model controls, privacy, and compliance considerations.
• Demonstrated ability to lead senior engineering teams, establish technical direction, influence executive stakeholders, and successfully deliver complex technical roadmaps.
• Strong software engineering background with production experience in Python and modern software architecture.
• Experience using AI-assisted software development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, or similar technologies to accelerate engineering productivity.
• Excellent communication and collaboration skills with the ability to influence both technical and business stakeholders.
Preferred Skills
• Experience building enterprise AI platforms within financial services, insurance, or another highly regulated industry.
• Experience with Vertex AI, LangChain, Google ADK, AutoGen, CrewAI, OpenTelemetry, and modern AI platform technologies.
• Knowledge of enterprise AI governance frameworks including NIST AI RMF, ISO 42001, SOC 2, HIPAA, GDPR, or emerging AI regulations.
• Experience leading greenfield platform initiatives and building high-performing engineering organizations.
Why This Role
• Build the foundation. Define the architecture, standards, and operating model for enterprise AI across New York Life.
• Lead a senior team. Join a small, highly experienced engineering organization where technical excellence, ownership, and collaboration are the norm.
• Work on frontier technology. Build production-scale agentic AI systems and AI platforms that solve meaningful business problems in a highly regulated environment.
• Create enterprise impact. Shape how AI is responsibly adopted across the company and deliver capabilities that will enable teams across the enterprise for years to come.
• Stay hands-on. Continue building, architecting, and shipping while leading a team of exceptional engineers.
Location
We are committed to attracting exceptional talent and will consider flexible work arrangements for the right candidate.
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.
Company Overview
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.
Our diverse business portfolio creates opportunities to make a difference across industries and communities—inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you’ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what’s next, and your growth powers it.
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.
Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.
Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees’ needs.
Job Requisition ID: 94418
Read More
VP Of AI Jobs by Experience Level
See All 66 VP Of AI Jobs
Find roles that match your experience and apply in just a few clicks.
Find VP Of AI JobsVP Of AI Job Market
Who's Hiring
Top Industries Hiring
- Insurance
- Banking & Financial Services
- Retail
- Science & Research
- Technology & Software
What Employers Look For
The qualifications that appear most often in VP of AI jobs.
- 10 or more years of experience in machine learning, data science, or AI engineering
- Demonstrated success leading and scaling cross-functional AI or data teams
- Experience deploying large language models or generative AI systems in production
- Strong executive communication and ability to present AI strategy to board-level stakeholders
- Proficiency with cloud AI platforms such as AWS SageMaker, Azure AI, or Google Vertex AI
- Bachelor's or advanced degree in computer science, statistics, or a related quantitative field
Tips for Your VP Of AI Job Search
Quantify AI impact on your resume
Hiring committees for vp of ai roles want outcomes, not responsibilities. Replace phrases like 'led AI initiatives' with specific results: reduced model inference costs, shortened deployment cycles, or expanded AI-driven revenue lines. Concrete numbers clear the first screening round.
Position your technical depth carefully
VP of AI candidates often get filtered out for being too hands-on or not hands-on enough. Read each job description to gauge whether the company wants a builder-leader who codes or a strategic executive who directs engineering teams, then frame your resume accordingly.
Align your portfolio to the company's AI maturity
A company building its first AI org needs a different vp of ai than one scaling a mature platform. Research whether the employer is pre-production, growing, or optimizing before your interview, and show examples from whichever stage matches theirs.
Apply early to roles that fit
Migrate Mate lists vp of ai openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a responsible AI narrative for interviews
Most vp of ai interview panels now include a dedicated round on AI governance, ethics, or risk frameworks. Have a clear position on model bias mitigation, data privacy, and regulatory readiness before you walk in. Generic answers on this topic cost candidates senior offers.
Negotiate equity tied to AI milestones
VP of AI compensation packages often include performance equity tied to AI adoption metrics rather than standard vesting. During negotiation, clarify how milestones are defined and measured so your upside isn't tied to ambiguous internal targets you can't control.
VP Of AI Jobs: Frequently Asked Questions
Which companies are hiring the most vp of ais?
The companies hiring the most vp of ais right now include Citi, State Street, and New York Life, with the largest share of openings in New York, California, and Texas, based on current listings on Migrate Mate as of August 2026. Demand is concentrated in companies undergoing AI transformation across technology, financial services, and healthcare sectors.
How many vp of ai jobs are remote?
About 79% of vp of ai openings are fully remote or hybrid as of August 2026, reflecting the executive nature of the role and the need for cross-functional collaboration. AI strategy and governance work tends to be more remote-compatible than roles requiring frequent hands-on lab or data center presence.
How do you become a vp of ai?
Most people who reach a vp of ai role start in machine learning engineering, data science, or AI research, then move into team leadership and eventually director-level positions overseeing multiple AI workstreams. Building a record of shipping AI products into production, presenting strategy to senior leadership, and managing budget and headcount are the steps that distinguish candidates who advance to the VP level from those who stay in individual contributor or mid-management tracks.
Can you get a vp of ai job with limited leadership experience?
A vp of ai role with no prior people-management experience is rare, but candidates who led informal AI task forces, directed vendor relationships, or owned an end-to-end AI product lifecycle sometimes break through. The strongest path for someone light on direct reports is to take a staff or principal AI architect role first, build a clear record of cross-functional influence, and use that as the bridge to a formal VP title.
What does the vp of ai interview process look like?
The vp of ai interview process typically starts with a recruiter screen, followed by a hiring manager conversation focused on leadership philosophy and AI strategy. Later rounds usually include a technical deep-dive with senior engineers or data scientists, a presentation of your AI vision or a case study to the executive team, and a final cultural and values discussion with the CEO or CPO. Reference checks and a written strategic brief are common at the offer stage.
Where can I find and apply to vp of ai jobs?
You can find and apply to vp of ai jobs on Migrate Mate, which lists current openings from across the United States. Find roles that fit your background and apply directly to each listing from the same page.
See All 66 VP Of AI Jobs
Find roles that match your experience and apply in just a few clicks.
Find VP Of AI Jobs