Corporate Vice President - Solution Engineering & Architecture

New York Life • New York, NY

3d • $185,000 - $264,500 • Hybrid

About The Position

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. New York Life is advancing strategic transformations designed to reimagine critical enterprise capabilities through business process redesign, modern technology, data, analytics, automation, and AI. The initial assignment for this role is AI-led OCIO / NYLIM Portfolio Management. This strategic initiative is focused on reimagining investment and portfolio-management capabilities through modern technology, data, analytics, and AI across areas including Portfolio Construction & Markets, Macro Research, Private Markets, Investments to FP&A, Business Leadership Reporting, Client Reporting & Distribution, and the PM360 experience. The transformation is being delivered through multiple domain workstreams and outcome-focused teams that bring together business leaders, Technology, Data & Analytics, Architecture, Engineering, Risk and Control functions, enterprise platforms, and strategic partners. The Corporate Vice President, Solution Engineering & Architecture provides senior technology and architecture leadership for New York Life’s strategic transformations, with accountability for translating future-state business and solution strategies into coherent, scalable, secure, and production-ready technology architectures. The initial assignment is AI-led OCIO / NYLIM Portfolio Management. The role owns solution engineering and architectural coherence across multiple domains and outcome teams within the assigned transformation. The leader establishes target-state architecture, reusable solution patterns, integration approaches, engineering guardrails, and reference implementations; resolves consequential cross-domain technology decisions; and uses hands-on solution engineering and rapid prototyping to validate critical architectural hypotheses before they are scaled through delivery teams. This is not a traditional architecture-governance role. The leader is expected to combine enterprise architecture judgment with practical solution engineering, moving from concepts and diagrams to working prototypes, proven patterns, and implementation guidance that accelerate delivery and reduce technology risk. Within AI-led Portfolio Management, the leader will shape the architecture that connects investment workflows, proprietary and market data, research, portfolio analytics, enterprise reporting, client and distribution experiences, and AI-enabled decision support across OCIO and NYLIM. The role operates with significant autonomy and influence across Domain Technology Leads, Business Discovery & Solution Strategy, Integrated Delivery, Data Architecture, Data Engineering, enterprise platforms, Cybersecurity, Risk and Control functions, and strategic technology partners. It is expected to make and influence decisions that span organizational boundaries and materially shape the technology direction of the transformation.

Requirements

• 15+ years of progressively responsible experience in software engineering, solution architecture, enterprise architecture, technology strategy, or related disciplines, including significant leadership responsibility for complex enterprise solutions.
• Demonstrated experience owning architecture or solution engineering across multiple applications, domains, platforms, or major transformation workstreams rather than a single solution or component.
• Proven ability to translate ambiguous business and product strategies into coherent target-state architectures, executable solution patterns, and production-ready technology approaches.
• Strong software engineering and architecture background spanning modern application development, APIs, integration, cloud platforms, distributed systems, data and analytics, security, observability, and enterprise architecture.
• Demonstrated experience making consequential technology decisions and resolving tradeoffs across scalability, performance, resiliency, security, cost, reuse, delivery speed, and long-term maintainability.
• Practical experience with generative AI, agentic systems, AI-assisted engineering, or related emerging technologies and an understanding of how these capabilities change application architecture and software delivery.
• Experience using prototypes, proofs of technology, or reference implementations to validate architecture hypotheses and accelerate delivery.
• Demonstrated success operating in large federated or matrixed enterprises and influencing senior technology leaders, engineers, architects, business stakeholders, and strategic partners across organizational boundaries.
• Experience partnering with Data Architecture, Data Engineering, Cybersecurity, Risk, enterprise platforms, and control functions to deliver secure and governed enterprise solutions.
• Strong experience with modern SDLC, Agile and Lean engineering practices, CI/CD, automated testing, production readiness, and operational supportability.
• Experience leading or providing technical direction to senior engineers and architects, including teams that may not report directly to the role.
• Strong executive communication skills with the ability to explain complex architecture decisions, options, and risks to both technical and nontechnical senior stakeholders.
• Enterprise Architecture Judgment — Ability to establish target-state architecture, evaluate options, and make pragmatic decisions that balance transformation speed with enterprise sustainability.
• Solution Engineering Leadership — Ability to move beyond architecture diagrams and use engineering, prototypes, and reference implementations to prove critical solution patterns.
• Systems Thinking — Ability to reason across business processes, applications, APIs, data, infrastructure, AI, security, controls, operations, and organizational dependencies as an integrated system.
• AI & Agentic Architecture — Strong understanding of modern AI application patterns, agent orchestration, retrieval, tool use, evaluation, observability, security, and human oversight.
• Technology & Engineering Depth — Broad technical competence with sufficient depth to challenge senior engineers and architects and guide difficult implementation decisions.
• Architecture Influence — Ability to create alignment across multiple technology organizations and strategic partners without relying solely on formal authority.
• Executive Communication — Ability to translate technical complexity into clear choices, implications, and recommendations for senior business and technology leaders.
• Strategic Decision Making — Ability to make high-quality technology decisions under ambiguity and incomplete information while maintaining momentum.
• Reuse & Platform Mindset — Ability to identify reusable patterns and shared capabilities while avoiding over-standardization that slows delivery.
• Risk & Production Mindset — Strong grounding in security, resiliency, controls, observability, operational readiness, and lifecycle management.
• Learning Agility — Ability to rapidly assess emerging technologies and determine their practical applicability and enterprise implications.
• 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 architecting investment-management, asset-management, portfolio-construction, research, private-markets, trading, client-reporting, or distribution technology capabilities.
• Experience with market and reference data, portfolio data, research content, document-heavy workflows, investment analytics, or enterprise reporting platforms.
• Experience designing architectures that combine structured and unstructured information, deterministic analytics, retrieval, and AI-enabled decision support.
• Experience within asset management, insurance, banking, capital markets, or broader financial services.
• Experience delivering AI-enabled transformation in a highly regulated enterprise.

Responsibilities

• Own target-state solution architecture and architectural coherence across multiple domains, products, and outcome teams within the assigned strategic transformation.
• Translate business and solution strategies into executable technology architectures, reference patterns, integration approaches, and engineering guardrails.
• Make and influence consequential architecture decisions spanning applications, APIs, integration, cloud, data, analytics, AI, security, controls, resiliency, and operations.
• Resolve cross-domain architecture conflicts and technology tradeoffs while balancing speed, reuse, scalability, cost, enterprise standards, and long-term sustainability.
• Establish clear architecture decision records, standards, and reusable patterns that enable delivery teams to move quickly without repeatedly solving the same problems.
• Maintain an enterprise perspective and identify opportunities to reuse platforms, services, data products, APIs, AI capabilities, and engineering patterns across workstreams and strategic bets.
• Use rapid prototyping and hands-on solution engineering to validate the most consequential technical assumptions before solutions are scaled through delivery teams.
• Mobilize engineers, Forward Deployed Engineers, strategic partner engineers, and domain specialists to prove architecture options, integration patterns, and emerging technology approaches.
• Move architecture from conceptual designs to working reference implementations and production-oriented patterns that engineering teams can adopt.
• Partner with Domain Technology Leads and engineering teams through implementation to ensure architecture intent is preserved while incorporating evidence and learning from delivery.
• Identify technical risks and constraints early and drive pragmatic mitigation before they become delivery bottlenecks.
• Define architecture patterns for AI-enabled and agentic applications, including orchestration, tool use, retrieval, memory, model interaction, human oversight, evaluation, observability, and operational controls.
• Establish patterns for how agents interact securely with enterprise applications, APIs, data products, documents, and workflow systems.
• Determine where deterministic software and data patterns are required and where agentic or probabilistic approaches can safely create differentiated business value.
• Shape reusable patterns for agent identity, authentication, entitlements, traceability, evaluation, guardrails, and human-in-the-loop decision points.
• Evaluate emerging integration and interoperability patterns, including API-based, event-driven, and agent/tool connectivity approaches, and determine where they are appropriate for enterprise use.
• Partner with AI platform and engineering teams to ensure domain solutions leverage enterprise AI capabilities while avoiding unnecessary duplication or lock-in.
• Shape architecture patterns that allow AI agents to augment investment research, portfolio analysis, private-market workflows, reporting, and distribution while maintaining provenance, entitlements, explainability, and appropriate human decision authority.
• Define the target-state solution architecture across Portfolio Construction & Markets, Macro Research, Private Markets, Investments to FP&A, Business Leadership Reporting, Client Reporting & Distribution, and PM360-related experiences.
• Establish patterns that allow investment professionals to securely combine proprietary NYL information, market data, research, portfolio data, documents, and enterprise systems without requiring unnecessary physical consolidation of every source.
• Shape architecture for investment decision workflows that require both deterministic analytics and contextual agentic retrieval, synthesis, explanation, and action.
• Partner with Portfolio Management Domain Technology Leads to resolve architecture dependencies across public markets, private markets, reporting, distribution, and Finance integration.
• Define integration and reuse patterns across investment platforms, data products, research repositories, enterprise reporting, APIs, AI services, and PM360 experiences.
• Ensure architecture supports traceability, provenance, entitlements, controls, and human judgment appropriate for investment and client-facing use cases.
• Partner closely with the Data Architect and Data Engineering teams while preserving clear accountability boundaries: Solution Engineering & Architecture owns end-to-end solution coherence, while Data Architecture owns target-state data architecture, semantics, lineage, and data-product patterns.
• Define application and integration patterns that enable trusted data to flow across systems and experiences with appropriate latency, security, resiliency, and observability.
• Partner with enterprise platform teams to select and reuse appropriate capabilities and to identify gaps that require new platform or shared-service investment.
• Guide build, buy, reuse, and partner decisions using clear architectural, engineering, business-value, cost, and risk criteria.
• Help establish a modern software delivery model built around strong specifications, rapid prototypes, AI-assisted engineering, automated testing, continuous validation, and disciplined production readiness.
• Define engineering patterns that enable small, senior teams to use AI-assisted and agentic development tools effectively while maintaining enterprise quality, security, controls, and traceability.
• Promote systems thinking among engineering teams, with emphasis on interfaces, failure modes, observability, operational support, and upstream/downstream impacts rather than isolated component delivery.
• Establish architecture and engineering quality bars that can be applied pragmatically across multiple outcome pods without creating unnecessary governance overhead.
• Serve as a senior technology advisor to business and Technology leaders, communicating architecture choices, tradeoffs, risks, and recommendations in clear business terms.
• Partner with Business Discovery & Solution Strategy leaders to ensure future-state business ambition is informed by technology possibilities without allowing current-state constraints to prematurely define the solution.
• Partner with Integrated Delivery and Domain Technology Leads to sequence architecture decisions and technical enablers in support of transformation roadmaps.
• Influence enterprise architects, platform leaders, Cybersecurity, Risk, Data, Engineering, and strategic partners without relying solely on formal authority.
• Provide technical leadership in high-ambiguity situations and drive timely decisions where multiple viable approaches, organizational boundaries, or enterprise constraints exist.
• Maintain an external perspective on modern architecture, AI engineering, cloud, data, and software-development practices and translate relevant developments into practical enterprise opportunities.
• 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.

Benefits

• leave programs
• adoption assistance
• student loan repayment programs

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed