Data/AI Engineer

Acrisure International Holdings, Limited Corp
Charing Cross, United Kingdom
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Charing Cross, United Kingdom

Tech stack

JavaScript
Artificial Intelligence
Computer Programming
Continuous Integration
Information Engineering
Dataspaces
Database Queries
Distributed Computing Environment
Python
TypeScript
Retrieval-Augmented Generation
Large Language Models
Spark
Event Driven Architecture
Information Technology
Data Analytics
Data Pipelines
Api Management
Databricks

Job description

  • Design and deliver scalable data pipelines using a mix of lowcode and codebased tooling to establish a robust, governed data foundation.

  • Translate complex insurance and brokerage workflows into scalable data and technology solutions, ensuring they are aligned to business processes and measurable outcomes.

  • Model core business concepts and relationships in a unified data model, using structured objects, links, transformations, and governed logic.

  • Build decision centric operational applications focused on business value, workflow efficiency, and KPI visibility, leveraging modern development frameworks and analytics tooling.

  • Develop and deploy safe, reliable, and auditable AIdriven solutions, including agents, automations, and decision-support capabilities, using appropriate governance, testing, and monitoring practices.

  • Collaborate with cross-functional technical and business teams to ensure solutions are scalable, reusable, and deliver clear return on investment

Requirements

  • 5-10+ years of experience building data-driven products

  • Demonstrated success delivering production use cases in regulated or data-sensitive domains (financial services or insurance preferred).

  • Strong coding experience in Python and TypeScript/JavaScript; SQL proficiency.

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field.

  • Equivalent industry experience building production-grade data and AI systems accepted.

Preferred Qualifications

  • Prior experience in the insurance domain, particularly in underwriting, placement, claims, or finance.

  • Familiarity with ML/LLM concepts such as retrieval-augmented generation, agent design, and human-in-the-loop models.

  • Demonstrated enablement leadership: building reusable templates, documentation, and coaching cross-functional teams.

  • Experience with event-driven architectures, API integrations, CI/CD, and infrastructure-as-code in cloud environments.

  • Effective communicator with a systems-thinking mindset and ability to translate business workflows into scalable solutions.

  • Exposure to Palantir Foundry and AIP is advantageous and will enhance your impact across our data ecosystem.

  • Advanced degree or certifications in cloud computing, AI/ML, data engineering, or solution architecture.

  • Familiarity with Spark, Databricks, or similar distributed processing frameworks.

About the company

A global fintech leader, Acrisure empowers millions of ambitious businesses and individuals with the right solutions to grow boldly forward. Bringing cutting-edge technology and top-tier human support together, we connect clients with customized solutions across a range of insurance, reinsurance, payroll, benefits, cybersecurity, mortgage services - and more. In the last twelve years, Acrisure has grown in revenue from $38 million to almost $5 billion and employs over 19,000 colleagues in more than 20 countries. Acrisure was built on entrepreneurial spirit. Prioritizing leadership, accountability, and collaboration, we equip our teams to work at the highest levels possible. Acrisure is seeking a Data/AI Engineer to join our growing team and focus on our International entities. In 2026, the primary focus will be the design and delivery of global KPIs across multiple international entities. This will involve integrating data from over 20 systems, establishing standardized KPI definitions, performing data transformation and modelling, and developing scalable dashboards and reporting solutions. Parallel and subsequent phases will focus on workflow automation, the rollout of AI-enabled capabilities, and broader operational optimisation initiatives.

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