AI Engineer

• Scale-Up Environment
• Permanent
• Flexible Hybrid: 1 - 2 days per week in Dublin 2

The Goal:

To shape and deliver the company's AI strategy: designing, building, and deploying machine learning and generative AI solutions that transform how the business operates and makes decisions.

The Role:

As an AI Engineer, you'll work in a team that takes ownership of the full AI lifecycle from proof of concept to production deployment. You'll work together to design scalable ML and GenAI systems in the Azure ecosystem, build reusable frameworks for model training and deployment, and ensure that AI is safely and effectively embedded across products and internal tools.

The Team:

You'll work closely with the Head of Data Engineering, Head of Analytics, and Product Engineering teams. You'll collaborate with stakeholders across product, operations, and strategy to identify high-impact AI opportunities and bring them to life.

You:

• 3-5+ years' experience in applied AI, ML engineering, or data science roles.
• Strong hands-on experience building and deploying models using Python, PyTorch or TensorFlow, and Azure ML.
• Experience developing end-to-end ML pipelines: data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
• Proven experience in LLM integration, fine-tuning, or retrieval-augmented generation (RAG) systems.
• Solid grounding in MLOps practices using Azure DevOps, Databricks, or similar.
• Strong SQL and Azure Data Factory experience for data sourcing and preparation.
• Excellent communication skills: able to explain complex concepts clearly to non-technical audiences.

Desirable:

• Experience working in small AI or data science teams.
• Familiarity with LangChain, OpenAI API, or Azure OpenAI Services.
• Exposure to vector databases, prompt engineering, and AI governance frameworks.
• Prior experience in a scale-up or innovation-driven environment where experimentation and delivery coexist.

The Offer:

• 95k-115k base salary, depending on relevant experience
• 20% Bonus
• Pension, health
• Stock options

Process: 3 stages (initial call, technical Zoom interview with team, and final onsite with senior leadership and product team)