Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Integration Engineer - GenAI | Insurance | DevOps

St Paul's
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Engineer

Data Engineer

Senior Data Engineer

Senior Data Engineer

Data Engineer

Integration Engineer - GenAI | Insurance | DevOps

Our client are an innovative provider of analytics based solutions to the insurance industry with cutting-edge Gen AI solutions. They currently have an urgent need for a Senior Integration Engineer with excellent client facing and API, Azure DevOps / CloudOps experience to lead onboarding and integration of their platform with their clients. Their advanced products streamline claims processing, enhance audit capabilities, and provide data-driven insights for smarter decision-making. As they grow, they're seeking a highly skilled Integration Engineer to ensure the seamless implementation and integration of their pioneering solutions into client systems.

Role Overview:

As an Integration Engineer, you will be instrumental in deploying Azure-based Gen AI insurance products. You will integrate our solutions with existing infrastructure, including document management systems, databases, and Guidewire platforms. This position demands technical expertise in system integration and cloud solutions, alongside a strong understanding of insurance technology. You will work closely with clients, troubleshooting and optimizing product performance. This pivotal role for our client will initially require 2 days per week, although is anticipated to grow with the business to being a full-time leadership function offering you the opportunity to become a key component of a FinTech start-up at the forefront of the Insurance analytics sector both in the UK and the US.

Key Responsibilities:

  • Integration Planning & Execution: Lead comprehensive integration projects of Gen AI insurance products into client systems.

  • System Configuration & Customization: Tailor solutions to meet specific client needs, ensuring compatibility with existing platforms.

  • API & Database Integration: Develop and manage APIs for seamless data exchange between systems.

  • Azure Deployment: Deploy and manage our products on Azure, optimizing performance and security.

  • Client Collaboration: Serve as the primary technical contact for clients during integration, offering support and training.

  • Testing & Validation: Conduct thorough testing to ensure compliance and functionality of integrations.

  • Documentation: Create and maintain detailed documentation for integration projects and best practices.

  • Post-Integration Support: Provide ongoing support and optimizations after deployment.

    Required Qualifications:

  • 5+ years of system integration experience, particularly with Azure-based solutions.

  • Proficient in API development and database management, especially with insurance technology.

  • Hands-on experience with Azure infrastructure including deployment and management of AI products.

  • Solid understanding of insurance technology, focusing on claims processing and document management.

  • Proven troubleshooting abilities with a proactive, independent approach to problem-solving.

  • Exceptional communication skills to engage clients effectively and explain complex concepts clearly.

  • Bachelor’s degree in Computer Science, Engineering, or a related field.

    Preferred Qualifications:

  • Experience with Gen AI or Machine Learning, particularly in insurance applications.

  • Azure or Guidewire integration certifications.

  • Background in an insurance technology or fintech startup

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.