AI Engineer

Company Description

Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Anthropic, Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services.

We’re an award-winning employer reflecting how our employees are at the very heart of what we do:

• UK & Ireland's premier AWS, Microsoft & Oracle partner
• 3300+ strong, €350/£300m revenue business
• 10+ years as a Great Place to Work in Ireland & UK
• Best Workplace for Women in the UK & Ireland by GPTW
• Best Workplace for Wellbeing in the UK by GPTW

We’re a core valuesdriven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you.

Job Description

We are seeking a hands-on AI/ML Engineer to build, deploy, and optimize machine learning and Generative AI solutions. The role focuses on developing production-grade AI applications, integrating AI models into business systems, and supporting the full AI development lifecycle.

The ideal candidate is passionate about modern AI technologies, software engineering best practices, and delivering reliable AI solutions at scale.

Key Responsibilities

AI Application Development

• Design, build, and maintain AI-powered applications and services.
• Develop and deploy Machine Learning and Generative AI solutions.
• Build Retrieval-Augmented Generation (RAG) systems and AI agents.
• Integrate foundation models and APIs into enterprise applications.
• Create reusable AI components and frameworks.

Machine Learning Engineering

• Train, fine-tune, evaluate, and deploy ML models.
• Develop feature engineering and model evaluation pipelines.
• Implement model monitoring and performance tracking.
• Optimize model inference performance and cost efficiency.

Generative AI Engineering

• Develop LLM-based applications and workflows.
• Build prompt templates, agent frameworks, and orchestration pipelines.
• Implement vector search and knowledge retrieval systems.
• Design evaluation frameworks for AI quality, safety, and reliability.
• Improve hallucination mitigation and response accuracy.

MLOps & Deployment

• Design and automate ML model training, validation, and retraining pipelines.
• Version and manage datasets, features, and model artefacts using tools such as MLflow or similar.
• Deploy and serve ML models via REST APIs or batch inference at scale on Databricks, Snowflake or similar.
• Monitor model performance in production, detecting drift and degradation.
• Manage feature stores and ensure data pipeline reliability for ML workloads.
• Implement experiment tracking and reproducibility across the model lifecycle.

Collaboration

• Work closely with Solution Architects, Product Managers, and Engineering Teams.
• Participate in code reviews and technical design discussions.
• Support testing, deployment, and ongoing optimisation activities.

Qualifications

Programming & Engineering

• Strong proficiency in:
• Python
• SQL

AI & Machine Learning

• Experience with:
• Scikit-learn
• PyTorch and/or TensorFlow
• Hugging Face
• Main AI services from leading cloud service and model providers
• Supervised and unsupervised learning
• Model evaluation
• Feature engineering
• Statistical concepts

Generative AI

• Practical experience building:
• RAG systems
• AI agents
• LLM-powered applications
• Vector search solutions
• Familiarity with:
• LangChain