Corporate Vice President - Portfolio Construction & Markets Technology

New York Life•New York, NY

1d•$185,000 - $264,500•Hybrid

About The Position

New York Life is advancing an AI-led transformation of Portfolio Management across OCIO and NYLIM, with the ambition of connecting proprietary investment expertise, portfolio information, market intelligence, data, analytics, and AI to improve investment decision-making across the enterprise. The Portfolio Construction & Markets domain brings together portfolio construction, asset allocation, portfolio monitoring, rebalancing, market and macro research, and related investment decision workflows. The opportunity is to move from fragmented information and episodic analysis toward more continuous, connected, and intelligence-enabled investment decision support. The Corporate Vice President, Portfolio Construction & Markets Technology provides senior end-to-end technology leadership for the Portfolio Construction & Markets domain within New York Life's AI-led Portfolio Management transformation. The leader is accountable for translating future-state investment capabilities into a coherent technology strategy, architecture, roadmap, and portfolio of executable outcomes spanning applications, data, analytics, AI, agentic capabilities, integration, engineering, controls, and production readiness. This is broader than an application development or program management role. The leader is expected to understand the investment decisions and workflows the technology must enable, challenge current-state constraints, and work across OCIO, NYLIM, Technology, Data & Analytics, Architecture, Risk, Compliance, and strategic partners to fundamentally reimagine how portfolio construction and market intelligence are delivered. A central part of the mandate is determining how AI and agentic capabilities can augment investment professionals by assembling relevant information, identifying signals and patterns, synthesizing internal and external perspectives, evaluating portfolio implications, and accelerating analysis while preserving investment judgment, transparency, provenance, and appropriate controls.

Requirements

15+ years of progressively responsible experience in technology, software engineering, solution delivery, digital transformation, investment technology, data/analytics, or related disciplines, including significant leadership responsibility in complex enterprise environments.
Proven experience owning end-to-end technology capabilities or major transformation domains from strategy through architecture, engineering, implementation, production, adoption, and measurable outcomes.
Demonstrated success operating in federated or matrixed enterprises and influencing senior business and technology stakeholders across organizational boundaries.
Broad technology and engineering background spanning modern application development, APIs and integration, data and analytics, cloud platforms, enterprise architecture, automation, and emerging technologies.
Strong understanding of generative AI, agentic technologies, and AI-assisted engineering and their practical application to enterprise workflows and software delivery.
Experience leading multidisciplinary technology teams and managing strategic partners, contractors, and federated resources.
Experience making consequential technology, architecture, investment, sequencing, and resource tradeoffs in complex transformation environments.
Experience operating within enterprise Risk, Security, Compliance, Audit, and control environments.
Strong analytical, communication, prioritization, systems-thinking, and executive-influence capabilities.
Domain Technology Leadership - Owns the complete technology capability for a major business domain, not simply an application portfolio.
Technology & Engineering Judgment - Evaluates solution approaches, architecture and data implications, engineering tradeoffs, and production risks.
Systems Thinking - Understands interactions across business workflows, applications, data, analytics, architecture, controls, and operating models.
AI-Enabled Transformation - Identifies where AI and agentic capabilities can materially change workflows, decisions, and delivery economics.
Executive Communication & Influence - Creates clarity, drives decisions, and influences senior stakeholders across organizational boundaries.
Strategic Planning & Execution - Converts future-state ambition into prioritized roadmaps, investments, sequencing, and executable outcomes.
Enterprise Delivery Discipline - Applies SDLC, Agile and Lean principles pragmatically with strong dependency, release, and production-readiness management.
Talent & Partner Leadership - Builds strong teams and integrates internal, federated, and external engineering capacity around common outcomes.
Risk & Control Judgment - Integrates security, data governance, compliance, auditability, and operational resilience into technology decisions from inception.
People Management – Develops and empowers talent through clear expectations, actionable feedback, effective coaching, and accountability, while fostering an inclusive, high-performing team environment.

Nice To Haves

Experience with asset management, institutional investments, insurance general account investments, or investment technology.
Familiarity with portfolio construction, asset allocation, investment research, risk, ALM, portfolio analytics, or trading/investment workflows.
Experience with market-data providers, portfolio-management systems, research platforms, or analytical tools.
Experience applying AI, analytics, or automation to investment decision-making.

Responsibilities

Own the end-to-end technology strategy and roadmap for Portfolio Construction & Markets across portfolio construction, asset allocation, portfolio monitoring, rebalancing, market and macro research, and related investment workflows.
Translate investment decision needs into scalable technology capabilities that can be reused across OCIO and NYLIM where appropriate.
Enable more continuous assessment of portfolios as market conditions, positions, cash needs, ALM constraints, risk considerations, and investment views evolve.
Integrate internal investment perspectives, external market information, research, portfolio data, and enterprise context into investment decision workflows.
Establish measurable technology and business outcomes tied to decision quality, speed, productivity, adoption, and investment effectiveness.
Reimagine investment workflows around what AI and agents can increasingly research, synthesize, monitor, analyze, and recommend.
Establish use cases for agents that monitor markets and portfolios, identify relevant changes, surface signals, synthesize research, and prepare analysis for investment professionals.
Determine where deterministic analytics and models are required versus where generative or agentic capabilities add value.
Ensure AI-generated insights maintain provenance to underlying sources and sufficient transparency for investment professionals to exercise judgment.
Partner with Risk, Compliance, and enterprise AI governance functions to support responsible deployment of AI in investment workflows.
Partner with the Portfolio Management Solution Engineering & Architecture Lead to define target-state solution architecture and reusable patterns.
Partner with the cross-bet Data Architect to define authoritative data sources, data products, semantics, lineage, provenance, freshness, and agentic access patterns.
Integrate portfolio positions, market data, economic data, ALM, risk, research, and other relevant information into the solution ecosystem.
Make consequential technology decisions across build, buy and reuse; APIs and integration; platforms; analytics; AI; and existing investment systems.
Ensure solutions are secure, scalable, observable, resilient, controlled, and production ready.
Partner with the Business Discovery & Solution Strategy Lead for Portfolio Construction & Investment Strategy to translate future-state workflows into executable technology roadmaps.
Contribute technology possibilities during discovery rather than waiting for requirements to be handed to Technology.
Use prototypes and rapid solution engineering to test difficult business and technology hypotheses before scaling.
Lead multidisciplinary outcome teams bringing together Product Owners, Forward Deployed Analysts, Forward Deployed Engineers, Obin AI engineers, investment SMEs, Data SMEs, and Risk/Control partners.
Manage technology capacity and strategic partners while maintaining NYL accountability for architecture, engineering quality, and institutional knowledge.
Partner directly with senior OCIO and NYLIM leaders to understand investment priorities and translate them into technology choices and investment decisions.
Navigate differing requirements across investment teams while identifying capabilities that should be common across the enterprise.
Ensure security, entitlements, information barriers, model governance, data controls, Compliance, and Risk requirements are incorporated from inception.
Establish transparent measures of delivery health, adoption, decision effectiveness, productivity, technology performance, and business value.
Build, lead and develop high performing teams with strong domain knowledge and modern technology and engineering capabilities.
Attract, develop and retain forward deployed and other high caliber technology talent, while building technology leadership and domain expertise across the organization.
Establish clear accountability and a culture of collaboration, innovation, engineering discipline and continuous improvement.
Lead effectively through both direct authority and matrixed relationships across Business, Product, Technology and partner teams.