At a Glance
- Tasks: Lead AI architecture strategy and implement scalable AI solutions for insurance clients.
- Company: Join Deloitte's innovative AI & Data service team in the insurance sector.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Inclusive culture with a focus on team development and career advancement.
- Why this job: Shape the future of AI in insurance and make a real impact on digital transformation.
- Qualifications: Proven experience in AI architecture and data science, with strong coding skills in Python.
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, Associate Director - Insurance, AI&Data, Technology & Transformation 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 technology and a network of industry leaders, making it an ideal place for those seeking meaningful and impactful careers in AI and data transformation.
Contact Details:
Hm Revenue & Customs (Hmrc) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Architect, Associate Director - Insurance, AI&Data, Technology & Transformation
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to AI and insurance. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Create a portfolio showcasing your AI projects, especially those relevant to insurance. Whether it’s a GitHub repo or a personal website, let your work speak for itself. This is your chance to shine!
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding of AI architectures. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Us!
Don’t forget to check out our website for openings at StudySmarter. We’re always on the lookout for talented individuals like you, so make sure to submit your application directly through us!
We think you need these skills to ace Lead AI Architect, Associate Director - Insurance, AI&Data, Technology & Transformation
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Lead AI Architect. Highlight your experience in AI architecture and any relevant projects you've worked on, especially those that align with insurance and digital transformation.
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. Mention specific technologies and methodologies you’ve used that relate to the job description, and don’t forget to show your passion for AI and its impact on the insurance industry.
Showcase Your Teamwork Skills:Collaboration is key in this role, so be sure to highlight your experience working with diverse teams. Share examples of how you've successfully led projects or contributed to team success, especially in cross-functional settings.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!
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 and technologies relevant to the insurance sector. Brush up on your knowledge of cloud-based AI/ML workloads and be ready to discuss how you would implement scalable solutions that align with client goals.
✨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 stakeholders. Highlight your experience in leading diverse teams and fostering an inclusive culture.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about AI/ML frameworks, coding in Python, and deploying models. Brush up on your knowledge of tools like TensorFlow and PyTorch, and be ready to explain your approach to MLOps capabilities and API integration.
✨Demonstrate Stakeholder Management Experience
Be ready to discuss your experience managing senior stakeholders and leading proposal development. Share specific instances where you’ve successfully navigated complex projects and how you ensured alignment with strategic goals during digital transformation efforts.
