Director, AI-Driven Applications

About the Role:

Grade Level (for internal use): 13

S&P Global Energy

The Role - Director, AI-Driven Applications

The Team: We are looking for a highly motivated, enthusiastic, and skilled engineering leader for S&P Global Energy. We strive to deliver solutions that are sector-specific, data-rich, and hyper-targeted for evolving business needs.

The Impact: S&P Global Energy is seeking a Director of AI-Driven Applications who is a senior strategic and hands-on technical leadership role responsible for defining and executing the organization’s vision for intelligent, AI-native enterprise systems. This role requires deep expertise in agentic AI design, large-scale data modelling, and enterprise solution architecture translating complex business challenges into scalable, production-grade AI solutions.

Responsibilities

• AI Strategy & Application Development
• Define the enterprise AI application strategy, roadmap, and governance frameworks aligned with business objectives
• Lead the design and delivery of production AI applications using LLMs, multi-agent systems, retrieval-augmented generation (RAG), and fine-tuning pipelines
• Architect end-to-end agentic AI workflows: autonomous planning, tool use, memory management, and multi-agent orchestration
• Evaluate and select AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, custom) appropriate to enterprise scale and security requirements
• Champion responsible AI principles - explainability, bias mitigation, auditability, and data privacy
• Data Modelling & Architecture
• Design and govern enterprise data models supporting AI feature engineering, vector embedding stores, knowledge graphs, and real-time inference pipelines
• Define ontologies, taxonomies, and semantic layers that enable AI systems to reason over structured and unstructured enterprise data
• Oversee the architecture of data platforms including data lakes, lakehouses, streaming pipelines, and feature stores
• Establish data quality, lineage, and observability standards to ensure model reliability in production
• Enterprise Architecture Leadership
• Own and evolve the enterprise architecture for AI integration across cloud, hybrid, and on-premise environments
• Drive architecture decisions across the full AI stack: model serving, API gateways, orchestration layers, observability, and security
• Align AI architecture with enterprise platforms and integration patterns (event-driven, microservices, API-first)
• Establish architecture review boards, design patterns, and reusable accelerators to scale AI delivery across business units
• People Leadership & Stakeholder Engagement
• Build, mentor, and lead a high-performing team of AI and Software engineers, data architects, and solution architects
• Partner with C-suite, business unit heads, and product leaders to identify and prioritize AI opportunities
• Represent the AI architecture function to executive stakeholders, board-level audiences, and external partners
• Drive a culture of continuous learning, experimentation, and engineering excellence
• Success Metrics (First 12 Months)
• Deliver an enterprise AI application roadmap adopted by executive leadership
• Ship at least two flagship agentic AI applications to production at enterprise scale
• Establish reusable AI architecture patterns and accelerators reducing delivery time by 30%+
• Build and grow a team of AI engineers and architects
• Define, publish, evangelize enterprise AI governance and data modelling standards

Basic Required Qualifications

• 12+ years of progressive experience in software/data/AI architecture with 5+ years in a leadership role
• Proven delivery of enterprise-scale AI or ML applications in production environments
• Deep expertise in at least two major cloud platforms (AWS, Azure, GCP) and associated AI/ML services
• Strong background in data modelling and data platform design (relational, NoSQL, graph, vector)
• Demonstrated experience architecting agentic AI solutions using LLMs and orchestration frameworks
• Excellence in stakeholder communication, able to translate technical concepts for executive audiences

Additional Preferred Qualifications

• Experience in regulated industries (financial services, healthcare, government) with AI governance requirements
• Published research, patents, or open-source contributions in AI/ML
• Certifications: AWS Solutions Architect Professional, Google Cloud Professional Data Engineer, or equivalen…