BENGALURU · FULLTIME
Lead AI Engineer
Brit Insurance
Bengaluru · onsite · Posted 64d ago
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Not disclosed7–11 yrsfulltimeBengaluru
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Section · 01
About this role
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.
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Section · 02
Skills
LanggraphLangchainAgentic AiGenerative AiMachine LearningLarge Language Models (LLMs)Microsoft AzureArtificial Intelligence