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S&P Global

Delivers credit ratings, market data, indices

Director – AI Solutions & Integration

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Engineering, or a related field is required; a master's degree or PhD in an AI/ML-related field is preferred.
  • At least 10 years of experience in AI/ML, data science, or advanced analytics roles.
  • At least 5 years of leadership experience managing technical teams and delivering AI/ML solutions at scale.
  • A proven track record of building and deploying production AI systems in complex enterprise environments.
  • Deep expertise in ETL/ELT design patterns, data pipeline architecture, and workflow orchestration frameworks.
  • Strong knowledge of batch and streaming data processing technologies.
  • Experience with modern data platforms, cloud infrastructure such as AWS, Azure, or GCP, and data engineering tools.
  • Proficiency in programming languages commonly used in data engineering, such as Python, SQL, or Scala.
  • Understanding of data quality frameworks, observability, monitoring, and alerting systems.
  • Knowledge of DevOps practices, CI/CD pipelines, and infrastructure-as-code.
  • Familiarity with data governance principles and compliance frameworks.
  • Strong leadership and team management skills, including the ability to inspire, mentor, and develop technical talent in emerging technologies.
  • Ability to collaborate across technical and business teams in a matrixed organization.
  • Ability to articulate complex AI concepts to non-technical audiences and translate business problems into AI solutions.
  • Ability to align AI initiatives with business objectives and drive innovation.
  • A problem-solving approach focused on practical, production-ready solutions.
  • The role is limited to persons with indefinite right to work in the United States.

Responsibilities

  • Own and drive the AI solutions enablement strategy, defining how value streams design, build, and scale AI applications that deliver measurable business value.
  • Establish reference architectures and standards for GenAI/LLM solutions, including RAG patterns, agentic workflows, orchestration, and integration into data pipelines, ensuring solutions are secure, governable, and production-ready.
  • Define and implement enablement programs for GenAI, LLM, and agent-based solutions across the organization.
  • Contribute to the broader Data AI & Enablement strategy, aligning AI capabilities with organizational strategic goals and data platform initiatives.
  • Represent Data at enterprise AI forums and advocate for AI capabilities and innovations.
  • Partner with PPD and value stream leadership to shape the AI roadmap, provide feasibility input, identify dependencies, and define success metrics and acceptance criteria for prioritized use cases.
  • Collaborate with stakeholders to identify high-value AI opportunities across Equity, Fixed Income, and Multi-Asset domains.
  • Balance innovation with pragmatism to ensure AI investments deliver tangible business outcomes.
  • Provide technical leadership on emerging AI technologies and their applicability to index management and data operations.
  • Co-develop AI applications with value stream subject matter experts, from prototyping through production deployment.
  • Establish prompt engineering and evaluation practices, including reusable prompt patterns, test harnesses, quality benchmarks, and regression approaches to prevent degradation over time.
  • Oversee the design and implementation of end-to-end AI solutions, including RAG pipelines, agentic workflows, and LLM-enabled applications.
  • Partner with the Data & AI Governance team to embed responsible AI practices and risk controls into every solution.
  • Ensure AI solutions are integrated with governed data and meet security and operational requirements.
  • Establish and maintain frameworks for AI solution monitoring, evaluation, and continuous improvement.
  • Drive standards for documentation, monitoring, cost controls, incident response expectations, and secure integration with enterprise platforms to ensure operational readiness for IT handover.
  • Partner with IT to support QA processes and early production stabilization.
  • Establish quality gates and definition-of-done criteria specific to AI solutions.
  • Lead, mentor, and develop a high-performing team of AI Solutions Leads and Experts.
  • Develop team capabilities and reusable assets, including starter kits, libraries, templates, office hours, and workshops, to accelerate adoption of AI patterns.
  • Collaborate with Data Integration & Workflows and Data Governance teams to ensure cohesive platform enablement.
  • Collaborate with PPD on AI roadmap prioritization, alignment with business requirements and strategic goals, technical feasibility assessments, and success metrics.
  • Partner with IT to ensure infrastructure readiness for AI workloads, smooth deployment of production-ready AI solutions, operational excellence, and clear support boundaries and service-level agreements.
  • Engage with data value stream subject matter experts to co-develop AI solutions aligned with business logic and domain expertise, and assess and develop their AI capabilities.
  • Collaborate with Data & AI Governance to embed responsible AI controls, conduct safety reviews, and ensure compliance with AI usage policies and risk management frameworks.
  • Partner with Data Integration & Workflows to operationalize AI data requirements, refresh cadences, and integration of AI solutions with data pipelines.
  • Own the technical strategy, standards, and execution approach for AI and advanced analytics initiatives.
  • Define and maintain reference architectures for GenAI, LLM, RAG, and agentic solutions.
  • Define and enforce the definition of done for production-ready AI solutions.
  • Establish scalable patterns and frameworks that enable multiple value streams to deliver AI solutions efficiently and consistently.
  • Embed governance, security, and ethical considerations into AI solutions to maintain organizational trust and compliance.
  • Reduce time-to-value for AI use cases through reusable components, clear standards, and effective enablement.
  • Ensure AI solutions deliver quantifiable business outcomes aligned with strategic priorities.
  • Attend at least one in-person interview at the final stage, ordinarily at the nearest S&P Global office, before an offer can proceed.

Desired Qualifications

  • Experience in financial services or quantitative modeling.
  • Experience across the breadth of index concepts and asset classes.
  • Familiarity with SPDJI products, methodologies, or index calculation processes.
  • Experience in Python or SQL development.
  • Experience in AI/ML technologies or cloud AI platforms.
  • Experience with Agile/Scrum methodologies and product-oriented delivery models.
  • Knowledge of data governance, data quality frameworks, and enterprise data architecture.
  • Experience building AI solutions for financial data, market data, or analytical workflows.

About the Company

S&P Global

Delivers credit ratings, market data, indices

S&P Global provides financial information and analytics for investors, corporations, and governments, including credit ratings, market data, and indices. It compiles large financial data, conducts research, and offers analytics, ratings, and benchmarks accessed via subscriptions, licenses, or transaction-based services. The company differentiates itself with an integrated suite that covers ratings, data, analytics, indices, and ESG solutions across global markets, backed by well-known brands. Its goal is to help clients make informed decisions, manage risk, and drive growth while prioritizing corporate responsibility.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1917

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