AI Engineer - FinOps

We are looking for a talented AI Engineer to join an international project for a global technology client, supporting enterprise organisations in delivering innovative AI-driven FinOps solutions.

As part of an international team, you will design, develop and implement AI and Generative AI solutions that enhance Cloud Financial Operations (FinOps), enabling organisations to optimise cloud spending, improve forecasting accuracy, automate financial processes and generate actionable business insights.

This role requires close collaboration with Cloud Architects, FinOps Consultants, Data Engineers and client stakeholders in a fast-paced, agile environment.

Key Responsibilities

• Design and develop AI-powered solutions for Cloud Financial Management (FinOps).
• Build Machine Learning and Generative AI applications to automate cloud cost analysis, forecasting, anomaly detection and optimisation.
• Develop and deploy scalable AI solutions using modern cloud-native architectures.
• Implement Retrieval-Augmented Generation (RAG), LLM integrations and AI Agents where applicable.
• Collaborate with multidisciplinary teams to define technical solutions aligned with business objectives.
• Integrate AI services with AWS, Azure or Google Cloud platforms.
• Apply MLOps best practices for model deployment, monitoring, governance and lifecycle management.
• Ensure security, scalability and responsible AI principles throughout the solution lifecycle.
• Stay current with emerging AI technologies and industry best practices.

Required Skills

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science or a related field.
• 4+ years of experience as an AI Engineer, Machine Learning Engineer or similar role.
• Strong programming skills in Python.
• Hands-on experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn.
• Practical experience working with Large Language Models (LLMs) and Generative AI solutions.
• Experience implementing RAG architectures and prompt engineering.
• Knowledge of LangChain, Semantic Kernel, AutoGen or similar AI orchestration frameworks.
• Experience with Azure OpenAI, OpenAI APIs, AWS Bedrock or Google Vertex AI.
• Strong understanding of MLOps practices and CI/CD pipelines.
• Experience with Docker, Kubernetes and containerised deployments.
• Experience with REST APIs and microservices.
• Good understanding of SQL and data engineering concepts.

Nice to Have

• Previous experience with FinOps or Cloud Financial Management.
• FinOps Certified Practitioner certification.
• Experience with Azure AI Foundry.
• Knowledge of Microsoft Fabric, Databricks or Snowflake.
• Experience with Infrastructure as Code (Terraform, Bicep, CloudFormation).
• Familiarity with cloud cost optimisation platforms such as CloudHealth, Cloudability, AWS Cost Explorer, Azure Cost Management or GCP Billing.
• Microsoft Azure AI, AWS Machine Learning or Google Professional ML certifications.

Soft Skills

• Excellent communication and stakeholder management skills.
• Strong analytical and problem-solving abilities.
• Client-focused mindset with consulting experience.
• Ability to work effectively within multicultural and distributed teams.
• Self-driven, proactive and adaptable.
• Passion for innovation and continuous learning.

What we offer

• Full remote work from anywhere in Europe.
• Competitive compensation - open to discussion and negotiable, with the possibility of a B2B contract.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science or a related field.
• 4+ years of experience as an AI Engineer, Machine Learning Engineer or similar role.
• Strong programming skills in Python.
• Hands-on experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn.
• Practical experience working with Large Language Models (LLMs) and Generative AI solutions.
• Experience implementing RAG architectures and prompt engineering.
• Knowledge of LangChain, Semantic Kernel, AutoGen or similar AI orchestration frameworks.
• Experience with Azure OpenAI, OpenAI APIs, AWS Bedrock or Google Vertex AI.
• Strong understanding of MLOps practices and CI/CD pipelines.
• Experience with Docker, Kubernetes and containerised deployments.
• Experience with REST APIs and microservices.
• Good understanding of SQL and data engineering concepts.

Nice to Have

• Previous experience with FinOps or Cloud Financial Management.
• FinOps Certified Practitioner certification.
• Experience with Azure AI Foundry.
• Knowledge of Microsoft Fabric, Databricks or Snowflake.
• Experience with Infrastructure as Code (Terraform, Bicep, CloudFormation).
• Familiarity with cloud cost optimisation platforms such as CloudHealth, Cloudability, AWS Cost Explorer, Azure Cost Management or GCP Billing.
• Microsoft Azure AI, AWS Machine Learning or Google Professional ML certifications.

Soft Skills

• Excellent communication and stakeholder management skills.
• Strong analytical and problem-solving abilities.
• Client-focused mindset with consulting experience.
• Ability to work effectively within multicultural and distributed teams.
• Self-driven, proactive and adaptable.
• Passion for innovation and continuous learning.

• Competitive compensation - open to discussion and negotiable, with the possibility of a B2B contract.