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 analysislossprojections premium calculations and price-impact modelling.

• Develop backend services and APIs using TypeScript/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/ 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.