Software Engineer (Generative AI and Innovation)

Role overview

Responsibilities

• check_circle Own medium-scale features and components end to end, from prototyping through to production-ready solutions, with senior guidance available when you need it
• check_circle Contribute to design discussions, bringing sound technical reasoning and viable suggestions to the table
• check_circle Build practical applications — AI-powered and otherwise — that address real business problems and deliver measurable value
• check_circle Work closely with colleagues across our Dublin and international Innovation teams, while taking initiative and contributing your own ideas
• check_circle Work in an Agile environment where you can experiment, learn quickly, and see the impact of your work
• check_circle Stay hands-on with the latest AI tools, models, and techniques, with ongoing opportunities to learn, test, and evolve
• check_circle Build and maintain evaluation harnesses and follow good practice in prompt engineering, experimentation, and solution design
• check_circle Create reusable components, tools, and patterns that help the wider team work more effectively and consistently
• check_circle Share what you learn, support technical quality, and help junior colleagues grow through code reviews and pairing

Basic qualifications

• Solid software engineering experience (typically 2–5 years), with a track record of delivering features independently
• Experience contributing to production-grade applications
• Hands-on experience with modern JavaScript/TypeScript development, including a framework such as React, Vue, or Angular
• Backend experience with Node.js, NestJS, or similar technologies
• Experience using Python to build AI-powered workflows, integrations, or applications
• Good understanding of APIs and integrating AI into real-world products and business processes
• Hands-on experience building with LLMs, including prompt design, tool use, and structured outputs
• Familiarity with RAG, retrieval pipelines, and embeddings
• Exposure to modern agent patterns and multi-step, tool-connected workflows
• Working knowledge of AWS and Kubernetes, and an interest in how AI applications are deployed and scaled
• Good communication skills, a practical and thoughtful approach to problem-solving, and the ability to work across engineering and business teams

Preferred qualifications

• Experience taking features from early experimentation through to production use
• Curiosity about emerging standards in the agent ecosystem, including Model Context Protocol (MCP)
• Exposure to vector databases and semantic search
• An eye for the quality, reliability, latency, and cost-efficiency of AI systems
• Exposure to AI evaluation frameworks, testing approaches, and guardrails for reliable and responsible AI
• A willingness to support others and contribute to engineering best practices

Benefits

• check_circle We help you be your best through professional development opportunities, interesting work and supportive leaders.
• check_circle We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
• check_circle Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

About the company