Lead AI Architect: Scalable GenAI & Data for Insurance

Job Overview

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.

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