New York Life Insurance Company
Jobs
Corporate Vice President - Release Train Engineer (RTE) - Agentic AI Web Application
New York Life Insurance Company
Corporate Vice President - Release Train Engineer (RTE) - Agentic AI Web Application
Be an Early Applicant
Leads an Agile Release Train delivering an agentic AI web application across product, engineering, AI/ML, architecture, security, QA, DevOps, and operations teams. Facilitates PI Planning, dependency and risk management, release readiness, production deployment, metrics, and continuous improvement. Coordinates AI experimentation and production delivery while addressing model reliability, safety, latency, cost, integrations, observability, and operational risks. Serves as the execution integrator between technical teams, product leadership, and enterprise stakeholders.
Location Designation: Hybrid - 3 days per week
Release Train Engineer (RTE) - Agentic AI Web Application Role Overview
We are seeking an experienced Release Train Engineer (RTE) to lead delivery of a next-generation Agentic AI web application. The RTE will serve as the delivery and execution leader across multiple agile teams responsible for building AI-powered user experiences, autonomous/agentic workflows, platform services, integrations, and production capabilities.
This role sits at the intersection of product, engineering, AI/ML, architecture, security, and operations, ensuring teams remain aligned on outcomes while managing the unique delivery risks associated with rapidly evolving generative and agentic AI technologies.
The ideal candidate combines strong SAFe/Agile program leadership with sufficient technical fluency to facilitate discussions involving LLMs, AI agents, APIs, cloud platforms, data, security, observability, and modern web architectures.
Key Responsibilities
Agile Release Train Leadership
• Lead and facilitate the Agile Release Train (ART) across product, web engineering, AI/ML, platform, architecture, security, QA, and DevOps teams.
• Facilitate PI Planning, ART Syncs, Scrum of Scrums, system demos, Inspect & Adapt sessions, and dependency/risk reviews.
• Partner with Product Management and Architecture to translate product strategy into executable PI objectives and delivery plans.
• Maintain visibility into milestones, dependencies, risks, impediments, and cross-team commitments.
• Drive predictable delivery without sacrificing experimentation and learning required for emerging AI capabilities.
• Coach teams and leaders on Agile/SAFe practices and continuously improve ART effectiveness.
Agentic AI Delivery
• Coordinate delivery of capabilities involving LLMs, AI agents, tool/function calling, retrieval-augmented generation (RAG), orchestration, memory/context management, and human-in-the-loop workflows.
• Manage dependencies between AI capabilities and traditional application components such as frontend, backend services, APIs, identity, databases, and enterprise integrations.
• Help teams distinguish between AI experimentation, production engineering, and product commitments, creating appropriate delivery mechanisms for each.
• Coordinate evaluation and readiness criteria for AI capabilities, including quality, accuracy, latency, reliability, safety, and cost.
• Facilitate resolution of issues involving model dependencies, prompts, agent behavior, data availability, integrations, and platform constraints.
Release & Production Readiness
• Coordinate end-to-end release planning across development, testing, security, infrastructure, and operations.
• Establish clear release readiness criteria and ensure teams address critical dependencies before production deployment.
• Partner with DevOps/SRE teams to strengthen CI/CD, automated testing, observability, rollback strategies, feature flags, and production monitoring.
• Ensure releases account for AI-specific operational considerations such as model availability, token consumption, latency, hallucination risk, agent failures, and third-party AI service dependencies.
• Facilitate post-release reviews and ensure production learnings are incorporated into subsequent planning.
Metrics & Continuous Improvement
Develop and maintain ART-level metrics covering:
• PI objective achievement
• Predictability and delivery confidence
• Feature/epic flow
• Cycle and lead time
• Dependency aging
• Defects and production incidents
• Release frequency
• Deployment success
• AI quality/evaluation results
• Reliability and latency
• AI/model usage and cost
Use metrics to identify systemic bottlenecks and facilitate measurable improvements rather than using metrics solely for status reporting.
Required Qualifications
• 10+ years of experience in Agile delivery, program management, technical program management, or engineering delivery leadership.
• 5+ years of experience functioning as an RTE, Senior Scrum Master, Agile Program Lead, or equivalent cross-team delivery leader.
• Demonstrated experience coordinating multiple engineering teams delivering complex enterprise applications.
• Strong knowledge of SAFe, Scrum, Kanban, Agile planning, dependency management, and release management.
• Experience working with modern web/application architectures, APIs, cloud platforms, CI/CD, and DevOps practices.
• Working knowledge of Generative AI and LLM-based application architectures.
• Ability to facilitate technical conversations among AI engineers, software engineers, architects, product managers, security teams, and business stakeholders.
• Strong executive communication, facilitation, conflict resolution, and stakeholder-management skills.
• Proven ability to identify systemic impediments and drive resolution across organizational boundaries.
Preferred Qualifications
• SAFe Release Train Engineer (RTE), SAFe Practice Consultant (SPC), or equivalent certification.
• Experience delivering Generative AI or Agentic AI applications.
• Familiarity with concepts such as:
o LLMs and foundation models
o AI agents and multi-agent architectures
o Prompt engineering and prompt management
o Tool/function calling
o RAG and vector search
o Agent orchestration
o AI evaluation frameworks
o Guardrails and Responsible AI
o AI observability
o Model/token cost management
• Experience with public cloud and AI platforms such as Azure, AWS, or Google Cloud.
• Experience delivering applications in a regulated enterprise environment.
• Familiarity with modern web architectures, microservices, event-driven systems, API ecosystems, and enterprise identity/security.
Key Competencies
Execution Leadership: Creates clarity across complex, interdependent teams and drives commitments through completion.
Technical Fluency: Understands enough of the AI and application architecture to identify dependencies, risks, and sequencing challenges without attempting to replace engineering leadership.
AI Delivery Mindset: Recognizes that AI development is probabilistic and experimental and adapts traditional delivery practices accordingly.
Systems Thinking: Identifies bottlenecks across the entire value stream rather than optimizing individual teams in isolation.
Facilitation: Builds alignment among product, engineering, AI, architecture, security, operations, and business stakeholders.
Risk Management: Proactively surfaces technical, operational, security, and AI-specific risks and drives them toward resolution.
Outcome Orientation: Focuses the ART on measurable customer and business outcomes rather than simply completing stories or maximizing velocity.
What Makes This RTE Role Different
This is not simply a ceremony-management or status-reporting RTE position.
The RTE is expected to act as the execution integrator for the Agentic AI product, connecting product intent with AI experimentation, software engineering, enterprise architecture, governance, and production operations.
The successful candidate will create enough structure to deliver a reliable enterprise product while preserving the experimentation and rapid learning necessary to build differentiated Agentic AI experiences.
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 hereto 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: 94751
#BI-Hybrid
Release Train Engineer (RTE) - Agentic AI Web Application Role Overview
We are seeking an experienced Release Train Engineer (RTE) to lead delivery of a next-generation Agentic AI web application. The RTE will serve as the delivery and execution leader across multiple agile teams responsible for building AI-powered user experiences, autonomous/agentic workflows, platform services, integrations, and production capabilities.
This role sits at the intersection of product, engineering, AI/ML, architecture, security, and operations, ensuring teams remain aligned on outcomes while managing the unique delivery risks associated with rapidly evolving generative and agentic AI technologies.
The ideal candidate combines strong SAFe/Agile program leadership with sufficient technical fluency to facilitate discussions involving LLMs, AI agents, APIs, cloud platforms, data, security, observability, and modern web architectures.
Key Responsibilities
Agile Release Train Leadership
• Lead and facilitate the Agile Release Train (ART) across product, web engineering, AI/ML, platform, architecture, security, QA, and DevOps teams.
• Facilitate PI Planning, ART Syncs, Scrum of Scrums, system demos, Inspect & Adapt sessions, and dependency/risk reviews.
• Partner with Product Management and Architecture to translate product strategy into executable PI objectives and delivery plans.
• Maintain visibility into milestones, dependencies, risks, impediments, and cross-team commitments.
• Drive predictable delivery without sacrificing experimentation and learning required for emerging AI capabilities.
• Coach teams and leaders on Agile/SAFe practices and continuously improve ART effectiveness.
Agentic AI Delivery
• Coordinate delivery of capabilities involving LLMs, AI agents, tool/function calling, retrieval-augmented generation (RAG), orchestration, memory/context management, and human-in-the-loop workflows.
• Manage dependencies between AI capabilities and traditional application components such as frontend, backend services, APIs, identity, databases, and enterprise integrations.
• Help teams distinguish between AI experimentation, production engineering, and product commitments, creating appropriate delivery mechanisms for each.
• Coordinate evaluation and readiness criteria for AI capabilities, including quality, accuracy, latency, reliability, safety, and cost.
• Facilitate resolution of issues involving model dependencies, prompts, agent behavior, data availability, integrations, and platform constraints.
Release & Production Readiness
• Coordinate end-to-end release planning across development, testing, security, infrastructure, and operations.
• Establish clear release readiness criteria and ensure teams address critical dependencies before production deployment.
• Partner with DevOps/SRE teams to strengthen CI/CD, automated testing, observability, rollback strategies, feature flags, and production monitoring.
• Ensure releases account for AI-specific operational considerations such as model availability, token consumption, latency, hallucination risk, agent failures, and third-party AI service dependencies.
• Facilitate post-release reviews and ensure production learnings are incorporated into subsequent planning.
Metrics & Continuous Improvement
Develop and maintain ART-level metrics covering:
• PI objective achievement
• Predictability and delivery confidence
• Feature/epic flow
• Cycle and lead time
• Dependency aging
• Defects and production incidents
• Release frequency
• Deployment success
• AI quality/evaluation results
• Reliability and latency
• AI/model usage and cost
Use metrics to identify systemic bottlenecks and facilitate measurable improvements rather than using metrics solely for status reporting.
Required Qualifications
• 10+ years of experience in Agile delivery, program management, technical program management, or engineering delivery leadership.
• 5+ years of experience functioning as an RTE, Senior Scrum Master, Agile Program Lead, or equivalent cross-team delivery leader.
• Demonstrated experience coordinating multiple engineering teams delivering complex enterprise applications.
• Strong knowledge of SAFe, Scrum, Kanban, Agile planning, dependency management, and release management.
• Experience working with modern web/application architectures, APIs, cloud platforms, CI/CD, and DevOps practices.
• Working knowledge of Generative AI and LLM-based application architectures.
• Ability to facilitate technical conversations among AI engineers, software engineers, architects, product managers, security teams, and business stakeholders.
• Strong executive communication, facilitation, conflict resolution, and stakeholder-management skills.
• Proven ability to identify systemic impediments and drive resolution across organizational boundaries.
Preferred Qualifications
• SAFe Release Train Engineer (RTE), SAFe Practice Consultant (SPC), or equivalent certification.
• Experience delivering Generative AI or Agentic AI applications.
• Familiarity with concepts such as:
o LLMs and foundation models
o AI agents and multi-agent architectures
o Prompt engineering and prompt management
o Tool/function calling
o RAG and vector search
o Agent orchestration
o AI evaluation frameworks
o Guardrails and Responsible AI
o AI observability
o Model/token cost management
• Experience with public cloud and AI platforms such as Azure, AWS, or Google Cloud.
• Experience delivering applications in a regulated enterprise environment.
• Familiarity with modern web architectures, microservices, event-driven systems, API ecosystems, and enterprise identity/security.
Key Competencies
Execution Leadership: Creates clarity across complex, interdependent teams and drives commitments through completion.
Technical Fluency: Understands enough of the AI and application architecture to identify dependencies, risks, and sequencing challenges without attempting to replace engineering leadership.
AI Delivery Mindset: Recognizes that AI development is probabilistic and experimental and adapts traditional delivery practices accordingly.
Systems Thinking: Identifies bottlenecks across the entire value stream rather than optimizing individual teams in isolation.
Facilitation: Builds alignment among product, engineering, AI, architecture, security, operations, and business stakeholders.
Risk Management: Proactively surfaces technical, operational, security, and AI-specific risks and drives them toward resolution.
Outcome Orientation: Focuses the ART on measurable customer and business outcomes rather than simply completing stories or maximizing velocity.
What Makes This RTE Role Different
This is not simply a ceremony-management or status-reporting RTE position.
The RTE is expected to act as the execution integrator for the Agentic AI product, connecting product intent with AI experimentation, software engineering, enterprise architecture, governance, and production operations.
The successful candidate will create enough structure to deliver a reliable enterprise product while preserving the experimentation and rapid learning necessary to build differentiated Agentic AI experiences.
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 hereto 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: 94751
#BI-Hybrid
New York Life Insurance Company New York, New York, USA Office




51 Madison Avenue, New York, NY, United States, 10010
New York Life Insurance Company Jersey City, New Jersey, USA Office
New York Life Insurance Company Jersey City, NJ Office

30 Hudson Street , Jersey City, New Jersey, United States, 07302
Similar Jobs at New York Life Insurance Company
Artificial Intelligence • Cloud • Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Lead planning, coordination, and delivery of multiple strategic programs and projects using Waterfall and Agile. Develop project plans, governance, status reporting, and dashboards; manage risks, dependencies, testing coordination, and stakeholder communications to ensure timely solution delivery.
Top Skills:
JIRAMS OfficeMicrosoft PowerpointMicrosoft Project
2 Days Ago
Artificial Intelligence • Cloud • Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Paid 10-week investment research internship supporting fixed-income research analysts and portfolio managers. Responsibilities include financial modeling, scenario analysis, bond portfolio surveillance, credit research, market data collection, dashboards, reporting, portfolio management projects, new deal analysis, and market research. Interns gain exposure to institutional investing, collaborate with investment professionals, and participate in training, networking, and a summer project.
Top Skills:
BloombergC++ExcelJavaPythonVBA
Artificial Intelligence • Cloud • Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Leads cloud platform engineering and site reliability initiatives across AWS, GCP, and Azure. Designs reusable Terraform infrastructure, governed platform patterns, CI/CD integrations, and full-stack solutions for applications, data platforms, and AI services. Establishes SRE practices including SLOs, SLIs, error budgets, observability, incident response, and cost optimization. Partners with application, security, architecture, and business teams; mentors engineers, facilitates technical reviews, resolves operational issues, and drives standardization and process improvement.
Top Skills:
.NetAgentic AiAmazon EksAPIsAWSAws CdkAzureC#Ci/CdCloudFormationFinopsGCPGitGithub ActionsHarnessJavaJavaScriptJfrog ArtifactoryKubernetesPowershellPythonRagSlo/SliSQLTerraformYaml
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory






