Corporate Vice President - Enterprise Reporting & Investments

New York Life•New York, NY

4d•$185,000 - $264,500•Hybrid

About The Position

This role provides senior end-to-end technology leadership for a critical cross-bet domain connecting AI-led Portfolio Management with Enterprise Plan to Perform (EPP). The leader is accountable for the technology strategy, architecture, data integration, analytics, reporting, AI capabilities, engineering, controls, and delivery required to connect investment activity and portfolio decisions with NII, earnings, capital forecasts, and enterprise leadership reporting. The role must establish trusted and explainable connections between investment and financial information, with strong emphasis on deterministic data, reconciliation, lineage, semantic consistency, controls, and traceability. The leader will also identify where AI and agentic capabilities can improve explanation, synthesis, investigation, scenario understanding, and leadership decision support. The role operates across OCIO, NYLIM, Finance, EPP, Technology, Data & Analytics, Architecture, Risk, Controls, and strategic partners, and is expected to resolve complex cross-organizational dependencies and technology tradeoffs.

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 investment accounting, FP&A, NII, capital, earnings forecasting, management reporting, or finance technology.
Experience integrating investment, portfolio, or asset-management data with Finance or enterprise planning capabilities.
Experience with governed reporting, semantic layers, reconciliation, lineage, and controlled financial data products.
Experience applying AI to financial analysis, management reporting, or decision support while maintaining deterministic controls.

Responsibilities

Own the technology strategy and roadmap connecting portfolio decisions, positions, cash flows, assumptions, and investment activity to NII, earnings, capital, forecasts, and related FP&A capabilities.
Create reliable, traceable technology patterns for moving investment information into Finance planning and modeling workflows.
Partner with EPP Planning & Projections, Financial Modeling, Performance Technology, and NEXUS Technology to ensure investment information is consistently represented and usable across enterprise financial decision-making.
Identify and resolve cross-bet dependencies involving data, timing, calculation logic, semantics, controls, and ownership.
Establish measurable outcomes tied to timeliness, reconciliation quality, decision support, reduction of manual handoffs, and improved integration between Investments and Finance.
Own technology capabilities supporting business leadership reporting across investment performance, product health, fundraising, investment-team updates, portfolio developments, and related management views.
Reimagine reporting from static production and distribution toward continuously available, governed, drillable, and explainable information.
Enable leaders to move from reported outcomes into underlying drivers, context, and relevant actions while preserving authoritative metrics and controls.
Identify opportunities for AI to synthesize commentary, investigate drivers, prepare briefing materials, and answer contextual questions using trusted enterprise information.
Ensure leadership reporting remains consistent with authoritative investment and Finance data and definitions.
Partner with the cross-bet Data Architect to define authoritative sources, data products, semantic models, lineage, reconciliation, freshness, and cross-bet data contracts.
Partner with both Solution Engineering & Architecture leads to define integration and application patterns across Portfolio Management and EPP.
Determine where data must be physically consolidated versus where governed federation or runtime access is appropriate, with particular emphasis on deterministic financial outputs.
Ensure traceability from source investment information through transformations, models, reports, and downstream Finance outputs.
Embed security, entitlements, controls, auditability, resiliency, and production readiness throughout the architecture.
Partner with Business Discovery & Solution Strategy leaders across both bets to define future-state reporting and Investments-to-FP&A workflows.
Use AI and agentic capabilities selectively for explanation, synthesis, anomaly investigation, contextual retrieval, and workflow acceleration while preserving deterministic financial calculations where required.
Use prototypes to validate user journeys, data availability, integration patterns, and decision-support concepts before scaling.
Lead multidisciplinary outcome teams involving Product Owners, Forward Deployed Analysts, Forward Deployed Engineers, Obin AI engineers, Finance and investment SMEs, Data SMEs, and Risk/Control partners.
Manage strategic partners and federated teams with clear accountability for quality, outcomes, and knowledge transfer.
Build trusted relationships with senior Investments, Finance, and Technology leaders and drive decisions across organizational boundaries.
Create transparency around cross-bet priorities, dependencies, tradeoffs, investment requirements, and delivery commitments.
Establish measures of data quality, reconciliation, reporting timeliness, adoption, workflow efficiency, and business value.
Ensure solutions support durable enterprise capabilities rather than bespoke reporting or one-off integrations.
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.