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-calibreteam 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 canoperateindependently 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 workflowsearlyand 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 similarlakehousepatterns.

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

• Implement front-end mathematical computations with precision, including exposure analysis,lossprojections, 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 andrecommendations clearlyto 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 workflowemerges, 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, includingNestJSor comparable backend frameworks used in production.

• Strong React skills, includingcomponentarchitecture, state management, and experience deliveringdata-heavyuser 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 andvalidatecomputations 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 domainexpertisein insurance, risk, and actuarial concepts.

• AI-native development experience, witha track recordof 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 datavisualisationincludingibrariessuch as D3, Recharts, or AG Charts.

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

• Priorworkon 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 modernlakehouseor 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, withadditionalbusinessexposurea plus.