Location: Madrid, M, ES

About the Team and Our Scope

We are a forward-thinking tech organization within Swiss Re, delivering transformative AI/ML solutions that redefine how businesses operate. Our mission is to build intelligent, secure, and scalable systems that deliver real-time insights, automation, and high-impact user experiences to clients globally. You'll join a high-velocity AI/ML team working closely with product managers, architects, and engineers to create next-gen enterprise-grade solutions. Our team is built on a startup mindset — bias to action, fast iterations, and ruthless focus on value delivery.
We’re not only shaping the future of AI in business — we’re shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions.

Role Overview

As an AI/ML Engineer, you will play a pivotal role in the research, development, and deployment of next-generation GenAI and machine learning solutions. Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You’ll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over both the technical stack and the emerging product direction.

Key Responsibilities

• Build Next-Gen GenAI Pipelines: Design, implement, and optimize pipelines across RAG, prompt engineering, long-context input handling, and multi-modal processing.
• Prototype, Validate, Deploy: Rapidly test ideas through PoCs, validate performance against real-world business use cases, and industrialize successful patterns.
• Ingest, Enrich, Embed: Construct ingestion workflows including OCR, chunking, embeddings, and indexing into vector databases to unlock unstructured data.
• Integrate Seamlessly: Embed GenAI services into critical business workflows, balancing scalability, compliance, latency, and observability.
• Explore Hybrid Strategies: Combine RAG with context-native models, retrieval mechanisms, and agentic reasoning to build robust hybrid architectures.
• Drive Impact with Product Thinking: Collaborate with product managers and UX designers to shape user-centric solutions and understand business context.
• Ensure Enterprise-Grade Quality: Deliver solutions that are secure, compliant (e.g., GDPR), explainable, and resilient — especially in regulated environments.

What Makes You a Fit

Must-Have Technical Expertise

• Proven experience with GenAI techniques and LLMs, including RAG, long-context inference, prompt tuning, and multi-modal integration.
• Strong hands-on skills with Python, embedding models, and orchestration libraries (e.g., LangChain, Semantic Kernel, or equivalents).
• Comfort with MLOps practices, including version control, CI/CD pipelines, model monitoring, and reproducibility.
• Ability to operate independently, deliver iteratively, and challenge assumptions with data-driven insight.
• Understanding of vector search optimization and retrieval tuning.
• Exposure to multi-modal models

Nice-To-Have Qualifications

• Experience building and operating AI systems in regulated industries (e.g., insurance, finance, healthcare).
• Familiarity with Azure AI ecosystem (e.g., Azure OpenAI, Azure AI Document Intelligence, Azure Cognitive Search) and deployment practices in cloud-native environments.
• Experience with agentic AI architectures, tools like AutoGen, or prompt chaining frameworks.
• Familiarity with data privacy and auditability principles in enterprise AI.

Bonus: You Think Like a Product Manager

While this role is technical at its core, we highly value candidates who are curious about how AI features become products. If you’re excited by the idea of influencing roadmaps, shaping requirements, or owning end-to-end value delivery — we’ll give you space to grow into it. This is a role where engineering and product are not silos. If you’re keen to move in that direction, we’ll mentor and support your evolution.

For Spain, the base salary range for this position is between EUR 42,000 and EUR 70,000 (for a full-time role). The specific salary offered considers:

• the requirements, scope, complexity and responsibilities of the role,
• the applicant's own profile including education/qualifications, expertise, specialisation, skills and experience.

In addition to your base salary, Swiss Re offers an attractive performance-based variable compensation component, designed to recognise your achievements. Further you will enjoy a variety of global and location specific benefits.

Eligibility may vary depending on the terms of Swiss Re policies and your employment contract.

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