About WTW Global Technology

Everything we do within WTW Global Technology has a global focus at its heart. We aim to provide colleagues with consistent technology, experiences and operations wherever possible.

The Role: Senior Director – AI Engineering

The Senior Director – AI Engineering will shape and deliver WTW’s central, enterprise-wide AI engineering capability as a senior expert within Global Technology. Working closely with Architecture, Information Security, lines of business, and business users, this role will provide senior technical advisory, define engineering direction, and establish the shared frameworks, reusable patterns, and reference implementations that enable teams across WTW to develop AI solutions safely, consistently, and at scale.

The role applies deep specialist knowledge of generative AI, agentic systems, enterprise platforms, and engineering governance to influence strategic decisions, guide complex technical delivery, and solve ambiguous problems across related disciplines. It has end-to-end ownership of both build and run activities for central AI engineering capabilities, ensuring solutions are secure, governed, reliable, and aligned to measurable business outcomes.

Key Responsibilities

• Shape the design, build, and ongoing support of WTW’s central AI engineering frameworks, providing reusable foundations for lines of business to build upon.
• Define technical direction for production-grade generative AI and agentic solutions across enterprise AI platforms, model providers, and orchestration frameworks, including:
  • Enterprise AI development and orchestration platforms, including agent frameworks, declarative and custom-engine agents, plugins, skills, connectors, and extensions.
  • Large language models and model-provider APIs, including tool use, governed integration patterns and protocols such as the Model Context Protocol.
  • Moveworks and other agentic automation and employee-support platforms.
• Establish shared patterns, reference architectures, SDKs, and reusable components, including prompt libraries, retrieval pipelines, and tool/connector catalogues, to accelerate safe AI adoption across the business.
• Act as a senior expert advisor to lines of business and business stakeholders, assessing workflow fit, validating use cases, and translating business needs into secure, scalable AI solution patterns.
• Partner with Architecture and Information Security to embed governance, responsible AI, and security controls into the AI platform by design, including identity, data protection, content safety, and auditability.
• Build and operate context engineering, retrieval-augmented generation (RAG), and agent orchestration capabilities, integrating enterprise data sources through secure, governed connectors.
• Define and implement large language model operations (LLMOps) practices, including evaluation, testing, prompt and model versioning, monitoring, and observability, to ensure quality, reliability, and cost efficiency in production.
• Serve as a senior technical escalation point for AI services, leading investigation, root cause analysis, and remediation of issues impacting production AI solutions.
• Influence adoption of new AI capabilities by coordinating technical messaging, implementation guidance, and alignment across impacted teams and lines of business.
• Create, maintain, and govern technical documentation, including design documents, architecture decision records, runbooks, and developer guidance for consuming central AI frameworks.
• Identify engineering and operational improvement opportunities, articulate recommendations, and lead delivery of improvement initiatives across the AI engineering practice.
• Guide and mentor AI engineers across WTW by sharing expertise, reviewing solution approaches, and setting engineering standards for building on central AI frameworks.
• Evaluate emerging AI technologies, tools, and platforms, and define adoption strategies and roadmaps for enterprise use.
• Maintain a strong information security and responsible AI posture, ensuring risk mitigation and adherence to data protection, model governance, and applicable regulatory requirements.
• Engage directly with business users and stakeholders to understand workflows, validate AI solutions in real-world contexts, and ensure capabilities deliver tangible business value.