AI Engineer

Who we are

Conclusion Lifecycle is the Managed Services brand of Conclusion Iberia, focused on delivering long-term, scalable IT services across the full lifecycle, from build to run.

It brings together the Managed Services operation that was previously part of Neotalent Conclusion, with a clearer focus on lifecycle ownership, operational excellence, and long-term partnerships.

Conclusion Lifecycle also acts as the incubator for new lifecycle-based service offerings within Conclusion Iberia, supporting clients with sustainable, resilient, and continuously evolving digital solutions.

Find out more about us at www.conclusionlifecycle.com.

Role Overview

We are looking for a Senior AI Engineer to integrate one of our Nearshore teams working remotely for international clients accross The Netherlands, Germany and other European countries.

In this role, you will take AI and machine learning solutions from development to production, building scalable, reliable, and secure AI systems. You will bridge the gap between Data Science and production environments, working with modern cloud platforms and cutting-edge GenAI technologies to deliver impactful, end-to-end solutions.

What you will do

• Operationalise AI/ML models and GenAI applications using tools such as Azure ML, MLflow, Databricks, and Kubeflow;
• Build and maintain production-grade AI services and APIs in Python (e.g. FastAPI), including testing, versioning, and deployment strategies;
• Design and implement GenAI solutions (RAG pipelines and agent-based systems) using frameworks such as LangChain and Hugging Face;
• Improve retrieval quality and performance through optimisation techniques (chunking, hybrid search, reranking, metadata filtering);
• Define and implement LLM evaluation frameworks, quality gates, and SLOs for latency, cost, and accuracy;
• Implement monitoring and observability for AI applications, including tracing, prompt management, and troubleshooting;
• Design secure and governed AI solutions, including guardrails, prompt injection protection, and data security controls;
• Deploy and manage LLM serving infrastructure and integrations with providers such as Azure OpenAI and others;
• Contribute to MLOps and LLMOps pipelines (CI/CD, model lifecycle, canary releases) and data pipelines (e.g. Airflow, dbt, Spark);
• Work with containers and orchestration (Docker, Kubernetes/AKS) and infrastructure as code tools;
• Collaborate with cross-functional teams to deliver end-to-end AI solutions and share best practices.

What you are like

• Highly experienced in AI/ML engineering and delivering production-grade solutions (MLOps/LLMOps);
• Proficient in Python and modern AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn;
• Experienced with Azure cloud services and AI platforms (Azure ML, Azure DevOps, Functions);
• Skilled in containerisation and orchestration using Docker and Kubernetes (AKS);
• Knowledgeable in CI/CD practices and Infrastructure as Code (Terraform, Bicep, or Pulumi);
• Hands-on experience with GenAI technologies (RAG, LLMs, LangChain, vector databases);
• Familiar with LLM evaluation, prompt engineering, and observability tools;
• Strong communicator able to engage both technical and non-technical stakeholders;
• Have good communication skills in English - as you waill collaborate daily with international teams.

Why join us

• Work on challenging projects for big clients
• Learn more about emerging technologies
• Possibility of working remotely
• Design your career plan
• Access to continuous training and certifications
• Evolve through our internal mobility program
• … and much more!