At a Glance
- Tasks: Lead AI architecture strategy and design scalable solutions for insurance clients.
- Company: Join Deloitte's innovative AI & Data service team.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Inclusive culture with excellent career development opportunities.
- Why this job: Shape the future of AI in insurance and make a real impact.
- Qualifications: Experience in AI architecture and data science is essential.
The predicted salary is between 90000 - 120000 £ per year.
Lead AI Architect in the Insurance practice at Deloitte’s AI & Data service offering. The role involves owning AI architecture strategy, designing, implementing, and operating scalable AI solutions for insurance clients.
Key Responsibilities
- Translate the vision of senior client stakeholders into AI/ML/GenAI architectural strategy and implementation roadmap, ensuring alignment with strategic goals and digital transformation efforts.
- Design, recommend, and implement end‑to‑end architectures that seamlessly integrate AI/ML solutions with existing insurance systems.
- Collaborate with Enterprise, Application, Data & DevOps Architects, Data scientists, MLOps & GenAI Engineers, and Business teams to pilot use cases and discuss architectural design.
- Select appropriate technologies from a pool of open‑source and commercial offerings, considering deployment models and integration with existing tools.
- Be responsible for the successful execution and operational improvement of AI‑powered applications using agile methodology.
- Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
- Develop and maintain contacts with top decision makers, lead proposal development, and contribute to pricing strategies.
- Manage diverse teams within an inclusive culture where people are recognised for their contributions.
- Develop the capability of junior team members through on‑the‑job training and formal development programmes.
Essential Qualifications
- Proven experience in architecture‑related disciplines.
- Experience in data science and understanding of math/statistical concepts relevant to AI/ML.
- Experience in implementing cloud‑based AI/ML workloads across one or more CSPs or third‑party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and SageMaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot.
- Experience in architecting scalable, performant & cost‑optimised AI/ML solutions leveraging serverless technologies, container/Kubernetes deployments, GPU compute infrastructure.
- Working knowledge of Generative AI and hands‑on experience in deploying and hosting Large Foundational Models.
- Experience with LLM architecture (e.g., Transformer, GANs, VAEs), fine‑tuning, retrieval‑augmented generation techniques and contextual embedding, vector‑database technologies and semantic search techniques & tools.
- Experience in writing robust and efficient code in Python.
- Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain.
- Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments.
- Experience in developing and integrating APIs, especially related to serving ML models.
- Experience building solutions that integrate with the enterprise to deliver end‑to‑end solutions, with the ability to recommend options and advise what is right for the use case.
- Ability to demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams.
- Ability to bring teams together and lead technical programmes to drive success through coaching, facilitation, stakeholder management and expectation management.
- Ability to lead go‑to‑market activities such as responding to RFI/RFPs and developing high‑quality proposal materials.
Desirable Qualifications
- Advanced degrees in Computer Science or Data Science or equivalent.
- Experience in insurance organisations or related consulting practices.
- Professional certifications in AI/ML technologies and cloud platforms.
Lead AI Architect: Scalable GenAI & Data for Insurance employer: Hm Revenue & Customs (Hmrc)
Deloitte is an exceptional employer for the Lead AI Architect role, offering a dynamic work culture that fosters innovation and collaboration within the insurance sector. Employees benefit from comprehensive professional development opportunities, including on-the-job training and formal programmes, while working in an inclusive environment that values diverse contributions. Located in a vibrant city, Deloitte provides access to cutting-edge technologies and a network of industry leaders, making it an ideal place for those seeking meaningful and impactful careers in AI and data.
Contact Details:
Hm Revenue & Customs (Hmrc) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Architect: Scalable GenAI & Data for Insurance
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or conferences related to AI and insurance. The more you engage with others, the better your chances of landing that dream job.
✨Show Off Your Skills
Don’t just talk about your experience; showcase it! Create a portfolio or GitHub repository with projects that highlight your AI architecture skills. This gives potential employers a tangible look at what you can do.
✨Ace the Interview
Prepare for interviews by practising common questions and scenarios related to AI architecture. Be ready to discuss your past projects and how they align with the role. Confidence is key, so rehearse until you feel comfortable!
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead AI Architect: Scalable GenAI & Data for Insurance
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Lead AI Architect role. Highlight your experience in AI architecture and how it aligns with the needs of insurance clients. We want to see how you can translate complex ideas into actionable strategies!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention your experience with cloud-based AI/ML workloads and any relevant tools like TensorFlow or PyTorch. We’re keen to see how you’ve implemented scalable solutions in past projects.
Demonstrate Collaboration:This role is all about teamwork, so share examples of how you've collaborated with diverse teams. Whether it's working with data scientists or business stakeholders, we want to know how you bring people together to achieve common goals.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Hm Revenue & Customs (Hmrc)
✨Know Your AI Architecture Inside Out
Make sure you’re well-versed in the latest AI architecture strategies, especially those relevant to insurance. Brush up on your knowledge of cloud-based AI/ML workloads and be ready to discuss how you would design scalable solutions that integrate seamlessly with existing systems.
✨Showcase Your Collaboration Skills
This role involves working closely with various teams, so be prepared to share examples of how you've successfully collaborated with data scientists, DevOps engineers, and business teams in the past. Highlight your experience in leading diverse teams and fostering an inclusive culture.
✨Demonstrate Your Technical Expertise
Be ready to dive deep into technical discussions about Generative AI, LLM architecture, and MLOps capabilities. Prepare to explain your hands-on experience with tools like TensorFlow and PyTorch, and how you’ve implemented robust AI solutions in previous roles.
✨Prepare for Stakeholder Management Questions
Since this position requires managing senior stakeholders, think of scenarios where you’ve effectively communicated complex technical concepts to non-technical audiences. Be ready to discuss how you’ve led proposal development and contributed to pricing strategies in past projects.
