Artificial Intelligence Engineer

Tenth Revolution Group; Helsinki; On-site; EUR 65,000 - 90,000; Full time

Job summary

Tenth Revolution Group is seeking an AI Engineer to design, build, and deploy scalable AI applications that advance products and processes. You will collaborate with software engineers, data professionals, and business stakeholders to deliver real-world AI solutions across Europe.

The role involves working with LLMs, RAG pipelines, AI agents, and cloud-native architectures to shape the company’s AI strategy and capabilities. Strong ML and MLOps experience is valued for production-ready outcomes.

Qualifications

• Several years of commercial experience in AI engineering, ML engineering, or data science.
• Hands-on experience with LLMs and Generative AI technologies.
• Experience with frameworks such as LangChain, LlamaIndex, CrewAI, or similar.
• Knowledge of RAG architectures and vector databases.
• Experience deploying solutions within Azure, AWS, or GCP environments.
• Understanding of ML workflows and MLOps principles.
• Experience building APIs and integrating AI services into software applications.
• Strong communication and stakeholder management skills.

Responsibilities

• Develop and deploy AI-powered applications and services.
• Design and implement LLM and Generative AI solutions.
• Build and optimise RAG pipelines using vector databases.
• Create scalable machine learning and data pipelines.
• Integrate AI models into production software environments.
• Evaluate, fine-tune, and monitor model performance.
• Work with cloud technologies to deploy and manage AI workloads.
• Contribute to AI best practices, architecture, and technical strategy.
• Stay informed on emerging AI trends, tools, and technologies.

Skills

AI engineering

Machine Learning engineering

Data science

LLMs & Generative AI

APIs integration

MLOps

AI architectures

Communication & stakeholder mgmt

Autonomous systems

CI/CD

Infrastructure as code

Tools

LangChain

LlamaIndex

CrewAI

Vector databases

Azure

AWS

GCP

Docker

Kubernetes

Job description

We're working with a growing technology organisation that is investing heavily in Artificial Intelligence and Machine Learning to build innovative products used by customers across Europe. They are looking for an AI Engineer to join a high-performing team focused on developing real-world AI solutions that deliver measurable business value.

This is an opportunity to work with the latest AI technologies including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and cloud-native architectures while helping shape the company's AI strategy and capabilities.

The Role

As an AI Engineer, you'll be responsible for designing, building, and deploying scalable AI applications that move beyond proof-of-concepts and into production. You'll collaborate with software engineers, architects, data professionals, and business stakeholders to create intelligent solutions that improve products and processes.

Responsibilities

• Develop and deploy AI-powered applications and services.
• Design and implement LLM and Generative AI solutions.
• Build and optimise RAG pipelines using vector databases.
• Create scalable machine learning and data pipelines.
• Integrate AI models into production software environments.
• Evaluate, fine-tune, and monitor model performance.
• Work with cloud technologies to deploy and manage AI workloads.
• Contribute to AI best practices, architecture, and technical strategy.
• Stay informed on emerging AI trends, tools, and technologies.

Required Skills

• Several of commercial experience in AI Engineering, Machine Learning Engineering, or Data Science.
• Hands-on experience with LLMs and Generative AI technologies.
• Experience with frameworks such as LangChain, LlamaIndex, CrewAI, or similar.
• Knowledge of RAG architectures and vector databases.
• Experience deploying solutions within Azure, AWS, or GCP environments.
• Understanding of machine learning workflows and MLOps principles.
• Experience building APIs and integrating AI services into software applications.
• Strong communication and stakeholder management skills.
• Docker and Kubernetes.
• AI Agents and Autonomous Systems.
• CI/CD and Infrastructure as Code.
• Experience working within a product-led technology environment.