Senior AI Engineer

We're looking for a Senior AI Engineer to join our team in Portugal in a fully remote working mode. In this role, you will help transform core insurance operations by developing intelligent, AI-powered solutions that automate complex workflows, reduce processing time, and enable strategic decision-making. You will work on designing, building, and deploying enterprise-grade AI systems leveraging LLMs, Retrieval-Augmented Generation (RAG), and agent-based frameworks to improve operational efficiency for global stakeholders.

This is an opportunity to drive innovation while ensuring reliability, scalability, and compliance for production-ready AI solutions.

Responsibilities

Identify opportunities for AI adoption within insurance operations and deliver production-ready solutions Design, develop, and deploy AI applications leveraging LLMs, RAG pipelines, and agentic workflows Build intelligent document processing, information extraction, and classification systems for insurance processes Define and implement AI evaluation frameworks for reliability, hallucination detection, and performance monitoring Own the complete AI solution lifecycle from ideation and prototyping through deployment and continuous optimization Drive rapid experimentation using modern development practices and emerging AI technologies Collaborate directly with functional teams including brokers and underwriters to ensure business alignment Implement frameworks for model observability, CI/CD automation, and secure data handling Mentor engineers, promote AI best practices, and champion operational excellence in production systems Research emerging trends and integrate cutting-edge AI technologies into enterprise-scale solutions Requirements Bachelor’s or Master’s in Computer Science, Engineering, or related field, or equivalent practical experience 5–8+ years of experience in software engineering, AI/ML, or applied machine learning roles Strong proficiency in Python and experience building AI-powered products from concept to production Hands-on knowledge of LLMs, Generative AI techniques, RAG, and agent-based AI workflows Familiarity with full-stack fundamentals and API design for AI applications Experience with CI/CD pipelines, containerization (Docker), and cloud platforms Strong understanding of monitoring practices, secure data handling, and AI risk considerations (cost, latency, accuracy) Excellent communication skills for bridging technical concepts with business objectives Nice to have Previous experience in insurance or financial services domain Exposure to multi-agent orchestration frameworks, fine-tuning LLMs, or model customization Understanding of vector databases and AI observability frameworks Familiarity with Kubernetes, Infrastructure as Code (IaC), and event-driven architecture Experience in distributed systems tracing, feature flagging, and progressive deployment strategies Knowledge of data engineering tools such as Spark, Databricks, or dbt Experience using AI-assisted development and providing mentorship in engineering teams