Full-Stack Engineer (Forward Deployed) - Digital Client Experience - Marsh

Marsh is hiring a Full-Stack Engineer to join our Innovation & Applied AI team within the DCX initiative, focused on building a market-leading digital platform. DCX operates like a startup within Marsh: a small, high-calibre team with the pace and autonomy of a startup, backed by the scale, reach, and data advantage of a global leader. This is an opportunity to drive meaningful transformation across a major enterprise, solving complex problems with high visibility and outsized impact. 

Our team is around 20 people, primarily based in London. We are looking for engineers who thrive in fast-moving environments and raise the pace and quality of execution. You will help build what we believe will become one of the largest data platforms in the insurance industry, alongside a sophisticated digital platform supporting renewal strategy, risk insight, and better client outcomes. 

This is a hybrid role primarily based in London, aimed at mid-to-senior engineers who can operate independently from day one and work closely with product, business, and technical leaders, though exceptional early-career candidates will also be considered. We are looking for a forward-deployed, AI-fluent engineer with strong judgment: someone who can work directly with users, quickly get to the heart of a problem, and turn it into a practical technical solution. You should be excited by the AI frontier, testing new models, tools, and workflows early and applying the ones that create real value. 

We will count on you to: 

• Own features end-to-end - from data consumption and querying through API logic to client-facing UI, with minimal handoffs and high autonomy. 

• Work directly with users and business stakeholders, joining calls, understanding pain points first-hand, shaping solutions collaboratively, and owning delivery through to measurable impact. 

• Self-source the data you need by navigating our data platform, writing SQL, understanding upstream structures, and working confidently with Databricks or similar lakehouse patterns. 

• Build and operate scalable, secure pipelines and curated data layers that power analytics, risk insights, and insurance recommendations. 

• Implement front-end mathematical computations with precision, including exposure analysis, loss projections, premium calculations, and price-impact modelling. 

• Develop backend services and APIs using TypeScript/Node.js, NestJS, or similar frameworks to support data access, computation, and model inference. 

• Build modern React experiences, including components, state management, and data-rich interfaces that explain insights and recommendations clearly to end users. 

• Integrate AI into your engineering workflow using tools such as Copilot, code generation, automated testing, and AI-assisted development practices to improve speed, quality, and throughput. 

• Stay on the frontier of AI - when a new model drops, a new harness appears, or a better workflow emerges, assess it early, experiment quickly, and bring the best ideas into user and client experiences where they create clear business value. 

• Build strong insurance and actuarial domain understanding so you can make product-informed engineering decisions and translate ambiguous needs into robust, production-ready software. 

What you need to have: 

• Strong experience in TypeScript/Node.js, including NestJS or comparable backend frameworks used in production. 

• Strong React skills, including component architecture, state management, and experience delivering data-heavy user interfaces. 

• Strong SQL and data querying skills, with the ability to self-serve from Databricks or similar data platforms. 

• Solid mathematical and quantitative skills, with the ability to implement and validate computations accurately. 

• Experience building APIs and services that connect data, computation, and user-facing applications. 

• High ownership, sound judgment, and comfort working from ambiguous requirements with minimal oversight. 

• Confidence working directly with users and stakeholders to understand problems and shape practical solutions. 

• Ability to learn quickly and build domain expertise in insurance, risk, and actuarial concepts. 

• AI-native development experience, with a track record of using AI tools daily, shaping AI-augmented engineering practices, and staying current with the fast-moving frontier of models, tooling, and techniques. 

What makes you stand out? 

• Experience with data visualisation including ibraries such as D3, Recharts, or AG Charts. 

• Experience building and shipping internal tools, automations, or AI-enabled workflows that delivered measurable business impact. 

• Prior work on pricing, underwriting, exposure, claims, or risk analytics products. 

• True full-stack range - comfortable moving from DevOps and data architecture through backend systems and complex logic to polished frontend delivery. 

• Familiarity with modern lakehouse or data engineering patterns and strong production practices across testing, observability, and performance. 

• Experience working in high-autonomy, startup-style environments where speed, judgment, and adaptability matter. 

• Experience working in highly embedded, user-facing engineering roles. 

• Ability to communicate clearly with non-technical stakeholders and frame technical work in business terms. 

• Academic depth in Computer Science or another STEM field, with additional business exposure a plus.