Lead AI Engineer

We are looking for a Lead AI Engineer to join our team. Our client is executing a far-reaching modernization of its insurance technology stack, pivoting from legacy tools toward next-generation, agent-based AI infrastructure. In this role, you'll be part of a team spread across multiple regions, working to develop intelligent platforms that take the complexity out of insurance operations, giving brokers greater capacity to focus on strategic priorities and deepen client connections. Responsibilities Discover practical applications for AI that can create measurable value across Insurance Broking functions Map out, engineer, and deploy large-scale AI platforms designed to cut through complexity in insurance-related tasks Develop AI-based tools built around LLMs, RAG, document management, data extraction, classification logic, and agent-oriented system structures Engage directly with brokers, underwriters, and operational staff to identify friction points and build solutions engineered to grow with demand Carry full ownership across the AI product lifecycle, from concept exploration and prototyping through to release, performance supervision, and iterative improvement Design comprehensive evaluation frameworks for AI platforms, encompassing benchmarking, real-time monitoring, and detection of hallucination-related errors Head up rapid-cycle experimentation while advancing modern approaches consistent with current AI engineering practices Drive improvements in operational throughput, shrink completion timelines, and lift business performance through intelligent automation methods Act as a guide and technical sounding board for other engineers, promoting solid practices in building trustworthy AI systems Monitor developments in the AI space and apply new capabilities toward resolving issues specific to insurance operations Requirements A Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline, or equivalent practical exposure At least 5 years of professional background in Software Engineering, AI/ML, Machine Learning, or fields of similar nature A minimum of one year spent guiding and managing development teams Confident, hands-on familiarity with Python and TypeScript Demonstrated experience shepherding AI-powered products from initial concept all the way through to full production rollout Applied experience working with machine learning models and Large Language Models (LLMs) in live, practical settings Familiarity with present-day software engineering practices, including CI/CD pipelines and containerized deployment models Strong capacity for analytical thinking, sound problem-solving judgment, and clear, assured communication Ability to distill technical subject matter into terms easily understood by non-technical business stakeholders Excellent English communication skills (B2 level or higher) Nice to have Familiarity with (Re)Insurance Underwriting Operations to build a deeper understanding of industry-specific workflows Working understanding of Infrastructure as Code, with particular focus on security considerations, to support dependable and protected environment configurations Previous professional exposure to the Insurance industry to strengthen the practical relevance of AI solution design Applied experience with Monitoring and Observability solutions to preserve ongoing insight into post-deployment system behavior Solid history of Technical Leadership, including guiding teams and shaping the broader direction of engineering efforts