Head of Multi-Asset Engineering

S&P Global•New York, NY

About The Position

The Head of Multi-Asset Engineering is responsible for the strategy, architecture, and execution of technology solutions supporting S&P Dow Jones Indices' Multi-Asset business. The role partners with Product, Research & Design, Operations, and Commercial teams to accelerate time-to-market, enable AI-powered product innovation, and build scalable capabilities for current and future Multi-Asset index offerings. The role combines value-stream ownership, engineering leadership, platform strategy, and organizational influence. The successful candidate will guide the shift from bespoke solutions toward reusable platforms and common services, while advancing modern product-centric engineering practices. This leader owns the Multi-Asset Index value-stream technology strategy and roadmap, drives product and platform delivery, develops shared-service and reuse strategies, applies AI and technology innovation, and leads engineering teams and cross-functional partnerships.

Requirements

15+ years of software engineering experience, including multiple years in an engineering leadership role with direct accountability for platform or product engineering organizations, distributed global teams, delivery roadmaps, and architecture governance.
Proven record of delivering business-critical technology solutions in capital markets, fintech, asset management, exchanges, market infrastructure, or financial data businesses.
Experience building reusable platforms, shared services, APIs, and enterprise-scale architectures using cloud-native engineering principles, modern SDLC/PDLC practices, and software delivery automation.
Experience delivering enterprise-scale, cloud-native platforms on AWS, Azure, or GCP, including microservices design, event-driven architecture, API gateway frameworks, and production-scale CI/CD pipeline automation.
Hands-on experience integrating AI/ML capabilities into production software delivery pipelines, including LLM-based tooling, automated code generation, or intelligent data processing, with measurable improvements to engineering throughput or product capability.
Bachelor's degree in Computer Science, Software Engineering, or a related engineering discipline.
Indefinite right to work in the United States.

Nice To Haves

Domain expertise in Multi-Asset, Equity, Fixed Income, Indices, Quantitative Finance, or Portfolio Construction strategies.
Experience with index lifecycle management platforms, back-testing systems, portfolio analytics tools, or custom index solutions such as ILMP, Index Studio, or equivalent enterprise index infrastructure.
Track record of modernizing legacy platforms and executing platform consolidation across distributed, multi-team engineering organizations.
Proficiency with modern SDLC/PDLC toolchains, software delivery automation, and quality engineering practices.
Advanced degree (Master's or PhD) in Computer Science, Financial Engineering, Mathematics, or a quantitative discipline.

Responsibilities

Lead the end-to-end technology strategy and execution roadmap for the Multi-Asset Index value stream, translating business growth opportunities into scalable technology capabilities.
Ensure technology investments align with business priorities, customer demand, and strategic objectives, and serve as the senior technology partner for Multi-Asset product development initiatives.
Accelerate delivery and improve time-to-market for new index launches and enhancements, including AI-enabled product capabilities, analytics, and data-package solutions.
Lead modern software engineering practices and product-oriented delivery models, establishing measurable outcomes for quality, resiliency, throughput, and business value.
Define and execute strategies for shared business services, APIs, frameworks, and engineering patterns.
Identify common capabilities across Index Build value streams and develop reusable solutions to reduce duplication and technical fragmentation across Multi-Asset, Equities, and Fixed Income technology platforms.
Promote adoption of common solutions across technology organizations.
Use AI, automation, and agentic development approaches to improve engineering productivity, evaluate emerging technologies, and expand platform capabilities.
Partner with Architecture, Data, and Platform teams to integrate AI-enabled capabilities into the full product lifecycle.
Lead, mentor, and develop engineering teams and technical leaders.
Influence cross-functional stakeholders and build partnerships across Product, Operations, Commercial, Data Platform, Architecture, Cyber, QE, and SRE teams.
Communicate strategy, priorities, risks, and outcomes clearly to senior leadership.