Senior AI Engineer (Hybrid; 80-100%)
About the Role
As a Senior AI Engineer at Swiss Re, you will take a leading role in designing and delivering advanced AI systems that address complex, real-world challenges in insurance and reinsurance. You will work at the intersection of AI engineering, workflow design, and business problem-solving, partnering closely with domain experts to translate ambiguous, document-heavy processes into robust, scalable AI solutions. Beyond individual contribution, you are expected to act as a force multiplier —shaping how we design systems, structure problems, and scale AI capabilities across the team.
Key Responsibilities:
- Design and implement end-to-end AI systems, from problem framing and data ingestion to deployment, evaluation, and monitoring in production
- Remain actively hands-on in coding, experimentation, and system design
- Architect and develop agentic and workflow-driven AI solutions, integrating LLMs, tools, and structured data across complex business processes
- Translate ambiguous business problems into well-defined, scalable system designs with clear outputs, evaluation criteria, and failure handling
- Lead the development of robust LLM-based applications (e.g., RAG systems, multi-step reasoning pipelines, document understanding systems)
- Stay at the forefront of emerging AI technologies and assess their applicability to reinsurance workflows and products
- Establish and promote best practices in AI engineering, including system design, evaluation frameworks, and MLOps
- Mentor and guide other engineers, contributing to raising the overall technical bar of the team
- Collaborate with data scientists, engineers, and business stakeholders across global teams to deliver impactful AI solutions
About You
You are an experienced AI engineer who combines strong technical depth with system-level thinking. You are comfortable operating in ambiguous environments and have a track record of turning complex problems into practical, production-ready solutions. You think beyond individual models or tools, focusing instead on end-to-end systems, reliability, and real business impact. You actively stay current with advances in AI and apply them selectively and pragmatically to real-world problems. You are deeply hands-on and enjoy building yourself—prototyping, coding, and iterating on solutions—while also guiding others and setting technical direction.
We are looking for candidates who meet these requirements:
- Advanced degree in computer science, artificial intelligence, machine learning, engineering, or related quantitative field
- 5–8+ years of hands-on experience building and deploying AI/ML systems in production environments
- Proven experience designing and implementing agentic or workflow-based AI systems, beyond simple prototypes or demos
- Strong expertise in modern AI techniques:
- LLM-based systems (prompt engineering, evaluation, reliability)
- Retrieval-Augmented Generation (RAG), vector databases, and embeddings
- Orchestration of multi-step AI pipelines and tool integration
- Practical understanding of model adaptation and fine-tuning
- Strong software engineering skills:
- Proficiency in Python
- Experience with scalable system design, testing, CI/CD, and code quality practices
- Experience with MLOps practices (model lifecycle management, monitoring, evaluation frameworks)
- Ability to structure and decompose complex problems, and communicate solutions clearly to both technical and non-technical stakeholders
- Experience working closely with business stakeholders and translating domain needs into technical solutions
- Experience in leading large, multi-locations delivery squads
Nice to have:
- Experience with the Palantir ecosystem
- Experience in insurance or reinsurance
- Exposure to large-scale, document-heavy or workflow-driven AI use cases