Applied AI Engineer

Senior Applied AI Engineer Location: Remote – Portugal, Spain or UK Based Salary: Competitive About the Role We are partnering with a consultancy specialising in the insurance sector that is looking for a Senior Applied AI Engineer to design, build and deliver production-ready AI solutions for enterprise clients. This role combines hands-on AI and machine learning engineering with Generative AI, data engineering and software development. You will work on practical solutions that are scalable, secure and measurable, helping clients move beyond proof of concept to deliver AI applications in real business environments. Key Responsibilities - Design and build applied AI and machine learning solutions for client projects. - Develop LLM-based applications, Retrieval-Augmented Generation (RAG) solutions, AI agents and workflow automation components. - Build and maintain data pipelines, feature pipelines, model training workflows and inference services. - Support the productionisation of AI and ML systems using MLOps and LLMOps practices. - Implement monitoring, evaluation, testing and observability for AI systems. - Integrate AI solutions with APIs, cloud services, data platforms and enterprise applications. - Collaborate with data scientists, data engineers, software engineers, architects and delivery teams. - Support technical discovery, solution design and client discussions where required. - Apply responsible AI principles, including security, privacy, governance, human oversight and cost control. - Contribute to reusable AI components, frameworks and delivery accelerators. Skills & Experience - Strong hands-on experience delivering AI, machine learning, data science or data engineering solutions. - Experience taking AI or ML solutions beyond proof of concept into production or production-like environments. - Strong Python skills and sound software engineering fundamentals. - Experience with machine learning techniques such as classification, regression, forecasting, clustering, anomaly detection, optimisation or segmentation. - Experience with Generative AI, LLMs, RAG, prompt engineering, tool use or agentic workflow design. - Good understanding of data pipelines, APIs, cloud-native architectures and CI/CD. - Experience with model evaluation, monitoring, versioning and deployment. - Experience working in client-facing or consultancy environments. - Strong communication skills, with the ability to engage effectively with technical and non-technical stakeholders. Technical Skills Experience with several of the following technologies is expected: - Python, Pandas, NumPy and Scikit-learn. - Machine learning libraries and tools such as XGBoost, LightGBM, CatBoost, Statsmodels, forecasting or optimisation libraries. - LLM platforms such as OpenAI, Azure OpenAI, Anthropic, AWS Bedrock or Google Vertex AI. - AI frameworks such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen or CrewAI. - Vector databases and search technologies such as Pinecone, Weaviate, Milvus, pgvector or Azure AI Search. - MLflow, Databricks, Unity Catalog, Databricks Model Serving and Feature Store technologies such as Feast. - Data platforms and pipelines, including Snowflake, Delta Lake, Apache Spark, Kafka, Confluent Cloud, Airflow or Databricks Workflows. - Cloud platforms including Azure, AWS or GCP. - Docker, Kubernetes, REST APIs, CI/CD and Terraform. - Monitoring and observability tools such as Prometheus, Grafana, ELK or OpenTelemetry. Desirable Experience - Experience in financial services, insurance, banking, payments, regulated industries or enterprise operations. - Knowledge of AI governance, model risk, data privacy, security or Responsible AI. - Experience supporting AI discovery, technical assessments or client workshops. - Experience developing reusable AI components, accelerators or internal frameworks. Benefits - Competitive salary package. - Remote working or Hybrid within Portugal, Spain or the UK. - Health and life insurance. - Financial support for personal development and training. - Flexible working environment. - Supportive team culture and opportunities for career development. - Relaxed dress code when working from the office.