Director, AI-Driven Applications
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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 equivalent
- Experience with TOGAF, Zachman, or other enterprise architecture frameworks
- What's In It For You?
- Our Mission:
- Advancing Essential Intelligence.
- Our People:
- We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding ne
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