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- Tasks: Lead the design of innovative AI platforms and solutions in a dynamic environment.
- Company: Join EXL, a global leader in data and AI with a collaborative culture.
- Benefits: Enjoy competitive salary, private healthcare, and professional development opportunities.
- Other info: Flexible hybrid working model and commitment to diversity.
- Why this job: Make a real impact in the insurance domain with cutting-edge AI technology.
- Qualifications: 10-15 years in software/AI engineering with strong architecture experience.
The predicted salary is between 80000 - 100000 £ 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.
We are seeking an experienced AI Solution Architect to lead the design and delivery of enterprise-scale agentic AI platforms and GenAI-enabled solutions. This role will define end-to-end architecture across AI, data, orchestration, integration, and platform layers, with a strong focus on scalable, secure, and explainable AI systems. The successful candidate will drive architecture strategy for multi-step agentic workflows, RAG frameworks, vector search, prompt lifecycle management, and enterprise integrations across structured, unstructured, and external data sources. You will work closely with AI, data, and engineering teams to establish scalable platform patterns, governance frameworks, and ModelOps capabilities while ensuring alignment with business and technical objectives. This is a hands-on leadership role requiring deep expertise in GenAI architecture, distributed systems, enterprise integrations, AI safety, and cloud-native engineering practices. The ideal candidate will combine strong technical depth with the ability to lead cross-functional teams, influence stakeholders, and translate complex AI capabilities into practical enterprise solutions.
As part of your duties, you will be responsible for:
- Architecture & Technical Leadership
- Define end-to-end architecture for agentic AI-enabled platform across data, AI, orchestration, and integration layers
- Design and govern agentic orchestration framework for multi-step workflows
- Establish architecture patterns for - RAG and grounding, Vector search and retrieval, MCP tool access layer, prompt management and evaluation
- Platform & Integration Design
- Define integration architecture across - Lakehouse, ODS, document systems; Underwriting systems and third-party APIs
- Design configurable, metadata-driven framework for multi-LOB onboarding
- Define API/microservices patterns (Python/.NET hybrid)
- AI & GenAI Enablement
- Define where and how to use - GenAI vs deterministic logic, agentic workflows vs pipeline workflows
- Establish multimodal integration approach combining structured, unstructured, and external data
- Design prompt lifecycle, evaluation, and optimization strategy
- Governance, Safety & ModelOps
- Define AI safety and guardrails (PII, hallucination control, policy constraints)
- Establish ModelOps and PromptOps frameworks
- Ensure explainability, auditability, and traceability of AI outputs
- Program Leadership
- Lead technical execution across AI, data, and platform teams
- Guide engineers (AI, data, full-stack) and ensure alignment with architecture
- Drive technical decisions and stakeholder communication
Qualifications and experience we consider to be essential for the role:
- Experience: 10–15+ years in software/data/AI engineering with 4–6+ years in AI/ML/GenAI architecture
- Background: Strong experience in designing enterprise-scale platforms and distributed systems
- Domain (good to have): Insurance/reinsurance / financial services
- Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field
- Profile Type: Hands-on architect with ability to balance strategy + execution
Technical skills:
- GenAI & Agentic Frameworks - Semantic Kernel/ LangGraph (or similar orchestration frameworks); LLM integration (Azure OpenAI, OpenAI APIs, etc.); Prompt engineering, prompt lifecycle design
- Retrieval & RAG - Azure AI Search (indexing, vector search, hybrid search); Embedding pipelines and retrieval optimization; RAG design, grounding strategies, context management
- Tool Access & Integration - MCP (Model Context Protocol) architecture and tool design; API design (FastAPI / REST / microservices); Integration with enterprise systems and third-party APIs
- AI Safety & Governance - NVIDIA NeMo Guardrails; Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control
- Evaluation & ModelOps - Azure AI Foundry (model hosting, versioning, monitoring); Evaluation frameworks (LLM-as-judge, test datasets); Prompt/version control, cost/latency monitoring
- DevOps & Observability - CI/CD pipelines (Azure DevOps / GitHub Actions); Logging, monitoring, observability (App Insights, etc.); Performance tuning and scalability
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 our employees with the tools and resources they need to succeed and excel in their careers.
- We offer 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.
As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status. 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.
Agentic AI Data Architect in London employer: exl
Contact Detail:
exl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Agentic AI Data Architect in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to AI architecture. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to AI and data architecture. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at EXL.
We think you need these skills to ace Agentic AI Data Architect in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Agentic AI Data Architect role. Highlight your experience in AI architecture and enterprise-scale platforms, and don’t forget to sprinkle in some relevant keywords from the job description!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. Share specific examples of your past work that align with the responsibilities listed in the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical skills! Make sure to mention your experience with GenAI frameworks, API design, and any other relevant technologies. This is your moment to impress us with your expertise!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way to ensure your application gets into the right hands and stands out to our hiring team!
How to prepare for a job interview at exl
✨Know Your AI Stuff
Make sure you brush up on your knowledge of GenAI architecture and distributed systems. Be ready to discuss specific projects where you've designed enterprise-scale platforms, especially in the insurance domain. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your Leadership Skills
Since this role involves leading cross-functional teams, prepare examples of how you've successfully guided engineers and influenced stakeholders in past projects. Highlight your ability to balance strategy with execution, as this is crucial for the position.
✨Understand the Integration Landscape
Familiarise yourself with integration architectures, especially around Lakehouse and third-party APIs. Be prepared to discuss how you've designed API/microservices patterns in previous roles, as this will demonstrate your technical depth and relevance to the job.
✨Emphasise AI Safety and Governance
Given the focus on AI safety and explainability, be ready to talk about frameworks you've implemented for PII detection and hallucination control. Discussing your approach to ModelOps and PromptOps will show that you take governance seriously, which is key for this role.