At a Glance
- Tasks: Design and govern AI architectures for intelligent automation in insurance using cutting-edge technologies.
- Company: Join EXL, a global leader in data and AI with a collaborative culture.
- Benefits: Enjoy competitive salary, private healthcare, flexible working, and professional development opportunities.
- Other info: Flexible hybrid working model and excellent career growth potential.
- Why this job: Make a real impact in the insurance industry with innovative AI solutions.
- Qualifications: Strong .NET/React skills and experience in AI integration are essential.
The predicted salary is between 70000 - 90000 £ per year.
EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 60,000 employees spanning six continents.
Location: London, United Kingdom (Flexible hybrid working) OR Fully Remote within the United Kingdom
Employment Type: Permanent
Summary of the role: As an AI Architect & .NET developer, you will be responsible for designing and governing end to end AI architectures on Azure ecosystem that enables intelligent automation and decision support across insurance functions such as underwriting, claims, reinsurance, and document heavy operations. The role focuses on building scalable, secure, and production grade GenAI platforms leveraging LLMs, Agentic AI, OCR to process complex unstructured insurance documents (e.g., loss runs, policy forms, claims reports) and generate accurate, explainable, and auditable outputs.
You will define architectural patterns, lead the implementation team, and partner with business and technology stakeholders to ensure AI solutions are enterprise ready, cost efficient, and aligned with regulatory and operational constraints.
As part of your duties, you will be responsible for:
- Act as an AI Architect and SME for GenAI‑driven insurance use cases
- Define end‑to‑end AI architecture for unstructured document ingestion, reasoning, and output generation
- Design LLM‑centric and hybrid AI architectures combining: OCR RAG systems Agentic workflows
- Design and govern prompt strategies and prompt frameworks for: Loss run and insurance document extraction & normalization Claims summarization, triage, and fraud signal generation Underwriting risk assessment and decision support
- Establish prompt versioning, testing, and optimization standards for enterprise use
- Architect Agentic AI systems for multi‑step reasoning, task decomposition, and tool orchestration
- Drive adoption of agent orchestration frameworks (LangGraph, AutoGen, CrewAI) in production scenarios
- Design RAG‑based knowledge architectures for policy, claims, and underwriting data
- Define chunking, embedding, retrieval, and grounding strategies
- Ensure traceability and explainability of generated outputs
- Drive architectural decisions related to: Scalability and performance Cost optimization of LLM usage Security, data privacy, and access control Auditability and regulatory compliance
- Define reference architectures and reusable components for multiple insurance use cases
- Establish evaluation frameworks for GenAI solutions, including: Precision, recall, and F1 metrics Grounding and hallucination detection Consistency and explainability checks
- Partner with business stakeholders (Underwriting, Claims, Actuarial, Legal) to shape AI roadmaps
- Guide and mentor .net developers, react developers, and GenAI developers
- Define best practices, standards, and architectural guardrails for GenAI adoption
Qualifications and experience we consider to be essential for the role:
- Strong proficiency in .NET/React
- Experience integrating AI solutions into enterprise systems
- .NET (Backend) and React (Frontend) Developer
- Prompt Engineering & LLM Design
- Retrieval Augmented Generation (RAG) Architectures
Skills and Personal attributes we would like to have:
- OCR systems for document ingestion and classification
- AI Governance & Token Economics
As part of a leading global Data and AI company, you can look forward to:
- A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension.
- EXL provides everyday financial well-being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers.
- We also offer a Cycle Scheme where you can save money on bikes and cycling accessories.
- At EXL, we are committed to providing a wide range of professional and personal development opportunities.
- We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge.
- From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies.
- EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP).
- At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration.
To be considered for this role, you must already be eligible to work in the United Kingdom.
AI Architect & .NET developer employer: exl
EXL is an excellent employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, we offer numerous opportunities for professional development and skill enhancement, particularly in the dynamic field of data analytics and insurance. Our commitment to work-life balance and a supportive environment makes EXL a rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architect & .NET developer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at exl or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to exl.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like exl.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like exl that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Architect & .NET developer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at exl.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at exl and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at exl
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If exl uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.