Speaker
Ryan Young
I began my career in technology at Maynooth University, where I completed a BSc in Computer Science and Software Engineering. Alongside my studies, I spent three years tutoring university students and working with young people through summer camps and youth programmes, teaching early programming concepts through tools such as Scratch. These experiences developed my communication, mentoring, and leadership skills, particularly my ability to make complex technical ideas easier to understand.
During university, I had the opportunity to work with Microsoft on early experimental AI systems. In 2023, I worked on AskAthena, an LLM-powered technical Q&A system developed with Microsoft mentorship and backed by Stack Overflow data. This gave me early hands-on experience with large language models and sparked a lasting interest in AI.
After graduating, I joined Workhuman as a Software Engineer within Platform Engineering, working with Java, AWS, Kafka, ActiveMQ, microservices, and distributed messaging. This gave me a strong foundation in backend engineering and taught me how large-scale systems communicate, fail, are monitored, and operate reliably in production.
At Workhuman, I was also able to return to my interest in AI by helping develop Quack, Workhuman’s internal agentic AI platform. Quack coordinates specialized agents and tools that interact with systems such as Jira, Confluence, and GitLab to support areas including product management, code review, development, and architecture. I contributed to the platform’s architecture and worked with technologies including AWS AgentCore, giving me practical experience designing agentic systems in an enterprise environment.
Alongside this, I introduced tools such as Claude Code and agentic coding workflows into my engineering work and team. I use agents not simply to generate code, but to explore unfamiliar codebases, trace distributed systems, investigate problems, understand architectural decisions, and accelerate development. This has significantly accelerated my growth as an engineer while reinforcing the importance of strong engineering judgement when working with AI.
Outside of work, I’m a big fan of video games and hands-on DIY projects. I’ve always enjoyed building things and figuring out how they work, whether that means experimenting with new technology, solving a problem in a game, or taking on a project at home. I enjoy starting with an idea or problem, working through the challenges, and ending up with something tangible.
During university, I had the opportunity to work with Microsoft on early experimental AI systems. In 2023, I worked on AskAthena, an LLM-powered technical Q&A system developed with Microsoft mentorship and backed by Stack Overflow data. This gave me early hands-on experience with large language models and sparked a lasting interest in AI.
After graduating, I joined Workhuman as a Software Engineer within Platform Engineering, working with Java, AWS, Kafka, ActiveMQ, microservices, and distributed messaging. This gave me a strong foundation in backend engineering and taught me how large-scale systems communicate, fail, are monitored, and operate reliably in production.
At Workhuman, I was also able to return to my interest in AI by helping develop Quack, Workhuman’s internal agentic AI platform. Quack coordinates specialized agents and tools that interact with systems such as Jira, Confluence, and GitLab to support areas including product management, code review, development, and architecture. I contributed to the platform’s architecture and worked with technologies including AWS AgentCore, giving me practical experience designing agentic systems in an enterprise environment.
Alongside this, I introduced tools such as Claude Code and agentic coding workflows into my engineering work and team. I use agents not simply to generate code, but to explore unfamiliar codebases, trace distributed systems, investigate problems, understand architectural decisions, and accelerate development. This has significantly accelerated my growth as an engineer while reinforcing the importance of strong engineering judgement when working with AI.
Outside of work, I’m a big fan of video games and hands-on DIY projects. I’ve always enjoyed building things and figuring out how they work, whether that means experimenting with new technology, solving a problem in a game, or taking on a project at home. I enjoy starting with an idea or problem, working through the challenges, and ending up with something tangible.