Lead AI Engineer

Requirements:

• Experience utilizing data science and machine learning with generative and agentic AI in a commercial environment, including demonstrable technical leadership and leading people, projects, or multidisciplinary delivery teams.
• Proven delivery of AI-powered applications from an ambiguous business problem to production operation, with evidence of measurable business impact and sustained adoption.
• Hands-on application of classical statistics, supervised and unsupervised machine learning, feature engineering, experimentation, and model evaluation.
• Hands-on delivery of generative AI and agentic solutions, including prompt design, RAG, embeddings/vector search, tool or function calling, orchestration, structured outputs, and failure handling.
• Experience selecting and combining pro-code and low-code/no-code approaches, including Microsoft Azure AI services and platforms such as Copilot Studio, Power Platform/Power Apps, Cytora, or comparable products, is desirable.
• Experience in a regulated, data-sensitive environment; insurance, reinsurance, or the London Market is advantageous.
• Strong ability to translate between scientific and business language for non-technical stakeholders; people leadership and ways of working
• Build and connect Brit India's AI community, fostering knowledge-sharing, reusable practices, and capability development, while ensuring close collaboration and alignment with the AI Enablement and AI UW Labs teams across India and the UK.
• Set clear goals and accountabilities, allocate work across both teams, and balance strategic delivery, experimentation, production support, and colleague development.
• Conduct regular one-to-ones and performance reviews; provide timely, evidence-based feedback, recognition, and coaching; create individual capability and development plans.
• Mentor engineers and scientists through pairing, technical reviews, and stretch opportunities; build depth across AI engineering, science, operations, and domain knowledge.
• Address delivery or behavioral concerns constructively, resolve conflict fairly and promptly, and foster psychological safety, inclusion, and effective cross-team collaboration.
• Support workforce planning, recruitment, onboarding, succession, and capability development; create reusable standards and communities of practice across Brit.

Skills

AI, Azure, GenAI, LLM, ML, Microsoft Azure, artificial intelligence, generative AI, machine learning