AI engineer

As the market leader for health and accident insurance software in Switzerland, Adcubum is driving the digital transformation of the insurance industry. Our steady growth is based on the consistent further development of innovative solutions designed by our experts at the interface between insurance knowledge and IT expertise. With locations in Switzerland, Germany and Croatia, we combine international perspectives with a local understanding of the industry - for insurance solutions that impress today and set standards tomorrow.

Are you passionate about building production-grade AI systems that solve real business problems? Do you have hands-on experience with LLM-powered applications and want to scale them to enterprise customers? Can you design intelligent agent systems and deploy them in a regulated industry?

Then you're the AI engineer we're looking for! Join us in transforming our internal AI Assistant into a multi-tenant SaaS product for insurance companies.

The Journey

We've built an agentic, RAG-based AI Assistant for Adcubum employees that has proven its value internally. Now we're taking the next step: transforming it into an external SaaS product for insurance companies.

As we establish our AI capabilities, you'll also help us explore and build further AI-powered solutions for the insurance industry - from automation to intelligent decision support.

You'll be part of a 4-person core team combining insurance domain expertise, product knowledge, and technical depth. Together, you'll work directly with product management and insurance companies to turn our internal solution into a customer-ready SaaS product.

What we're building:

• Multi-agent AI system with intelligent orchestration
• RAG pipelines integrating multiple knowledge sources (documentation, APIs, databases)
• Multi-tenant SaaS architecture for insurance companies
• Production-grade deployment with enterprise security and compliance

Support you'll have: You'll work closely with our experienced platform and DevOps teams for Azure infrastructure setup and deployment automation - but you should understand these concepts and contribute to architectural decisions.

Your tasks

Core AI Engineering Focus:

• Design and implement RAG pipelines with semantic search and knowledge retrieval
• Build multi-agent orchestration systems with intelligent query routing
• Integrate multiple LLM providers (Azure OpenAI, AWS Bedrock) and develop prompt engineering strategies
• Develop specialized knowledge base indexers for documentation, code, and business data
• Implement vector search combined with structured database queries
• Build REST APIs and integrate Model Context Protocol (MCP)
• Optimize AI system performance, accuracy, and cost efficiency

Production & Platform Collaboration:

• Collaborate with platform team on multi-tenant architecture design
• Contribute to Azure/AWS deployment decisions
• Implement monitoring, logging, and observability for AI components
• Work on containerization and deployment automation
• Support security, authentication, and compliance requirements
• Participate in customer discussions to understand requirements and iterate on solutions

• 3+ years of software engineering experience with strong Python backend development
• Hands-on experience building LLM-powered applications in production
• Practical experience with either:

• RAG systems (Retrieval-Augmented Generation), OR
• Other production ML/AI systems with real user impact

• Working knowledge of vector databases and embedding models
• Understanding of agent-based systems, multi-step AI workflows, or complex prompt engineering
• Experience with cloud platforms (Azure or AWS) - at least one production deployment
• Solid API design and development skills (REST, OpenAPI, async patterns)
• Basic understanding of containers and CI/CD concepts

Strong Advantages:

• Experience scaling AI systems to multi-tenant SaaS products
• Knowledge of Kubernetes or managed container services (AKS, EKS, ECS)
• Familiarity with Infrastructure as Code (such as Terraform)
• Understanding of Model Context Protocol (MCP)
• Node.js/TypeScript experience for full-stack integration work

Education & Languages:

• Bachelor's degree in Computer Science, AI/ML, or equivalent practical experience
• English language skills (fluent) - our product and customer communication is in English

Personal Skills

• Self-starter with ownership mentality: You like to see projects through from concept to production
• Pragmatic problem-solver: You balance quality with speed to market and make thoughtful technical decisions
• Comfortable with ambiguity: You thrive in environments where not everything is defined and you help shape the direction
• Team-oriented collaborator: You work effectively with domain experts, consultants, and customers who may not be technical
• Curious and learning-focused: AI/ML technology evolves rapidly - you stay current and love experimenting
• Customer-minded: You understand that technology serves business needs and enjoy seeing real-world impact

• End-to-end ownership: Shape a product from internal tool to external SaaS - your decisions matter
• Modern AI/ML stack: Work with cutting-edge technologies (multi-agent systems, RAG, latest LLMs)
• Small, high-impact team: Work directly with domain experts, product management, and customers
• Technical growth: Expand both your AI/ML expertise and cloud/platform engineering skills
• Production impact: Build systems used by insurance companies with thousands of users
• Professional development opportunities: Conferences, training, certifications in AI/ML space
• Collaborative environment: Learn from insurance domain experts while contributing technical expertise
• Flexible working arrangements: Modern work culture with flexibility
• Competitive compensation package: Aligned with your experience and the Croatian market
• International exposure: Work with teams across Switzerland, Germany, and Croatia