Forward Deployed AI Engineer

At WTW, you’ll be part of our Health, Wealth & Career (HWC) segment—where we use data, technology, and deep expertise to shape the future of work.

You’ll collaborate across multiple lines of business—such as Retirement, Health & Benefits, and Workforce Strategy—gaining exposure to diverse challenges and opportunities.

As the role evolves, you’ll also help deliver innovative, AI-driven solutions directly to external clients, turning complex problems into scalable outcomes.

Together, we’re creating more resilient, high-performing organizations—enhancing wellbeing, enabling better decisions, and driving sustainable business success at scale.

This is a hybrid role, with the flexibility of remote working alongside occasional time in the office to build strong relationships and collaborate effectively with stakeholders.

The Role This position is ideal for an experienced Staff Engineer, or Technical Lead with a strong enterprise engineering background and a passion for applying it to AI-enabled systems. You’ll bring deep expertise across modern full-stack technologies (.NET, Azure, SQL, React/Angular), along with experience in distributed systems, observability, and AI tooling such as LLMs, retrieval pipelines, agentic workflows, and platforms such as Anthropic Claude. Experience designing and deploying AI agents, leveraging Model Context Protocol (MCP), and orchestrating enterprise-grade AI solutions will be highly valued.

Acting as a bridge between business and technology, you’ll work across product, data science, architecture, and engineering teams, mentoring others, resolving production challenges, and scaling prototypes into robust, enterprise-grade solutions that deliver measurable business impact.

AI solution delivery: Design and build AI-enabled applications, copilots, agents, extraction pipelines, prediction interfaces, and decision-support tools using foundation models, retrieval-augmented generation, structured outputs, and orchestration frameworks.

Forward deployed problem solving : Work directly with business teams, product owners, clients, or operational users to understand real workflows, constraints, data quality issues, and adoption barriers, then translate these into working technical solutions.