Senior Software Engineer – Agentic AI | Shape a New AI Team at Scale
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At a glance
- Employment type
- Full-time
- Workplace
- Hybrid
- Category
- Full-stack
Technologies & skills
Primary technologies
Cloud & infrastructure
Other technical skills
What you'll be doing
Join a new Agentic AI team as a Senior Software Engineer to design and build production AI agents and workflows at scale. Work with LLMs, APIs, cloud, and Kubernetes, owning projects end-to-end and shaping technology and engineering standards. Hybrid role based in Cork, Ireland.
- Design and build production AI agents and agentic workflows
- Develop scalable software using Python, TypeScript or JavaScript
- Integrate LLMs with APIs, databases and enterprise systems
- Contribute to architecture and technical design
- Own features across the full SDLC, from design to deployment
- Build testing, observability and monitoring into AI applications
- Debug and optimise agent reliability, performance and quality
- Contribute to CI/CD, Kubernetes and cloud infrastructure
Key requirements
Must-have
- Proven experience building full-stack software at scale, ideally 1M+ users
- Commercial experience with AI/ML, LLMs or AI agents
- Strong Python, TypeScript or JavaScript skills
Role signals
- Technical focus
- full-stack software, AI agents, architecture, scalability
- Architecture / system design
- Indicated in the listing
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
Senior Software Engineer – Agentic AI | Shape a New AI Team at Scale
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Build the next generation of AI agents at massive scale
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Join a brand-new, high-growth AI engineering team shaping agentic experiences
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Work on AI solutions reaching millions of people globally
We are looking for a Senior Software Engineer to join an exciting new Agentic AI / AI Experiences team building the next generation of intelligent software experiences at global scale.
This is a rare opportunity to join a newly established engineering team at the forefront of enterprise AI. You’ll work on production-grade AI agents and agentic workflows that move beyond traditional chatbots, enabling AI to understand business processes, interact with enterprise systems, make decisions, and take meaningful actions on behalf of users.
The platform and products you’re helping build have the potential to reach millions of people, allowing you to work on challenging engineering problems where AI, software architecture and real-world user experiences come together.
You’ll have significant ownership from design through production, working closely with product managers, business stakeholders and engineers to turn ambitious AI concepts into reliable, scalable products. The team is growing rapidly, making this an excellent time to join and play a key role in shaping both the technology and engineering culture.
Why Join This Team
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Join a new, rapidly growing AI team building the future of agentic experiences
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Build AI solutions with the potential to reach millions of users globally
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Work across LLMs, agentic AI, RAG, cloud, APIs and Kubernetes
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Own projects end-to-end, from architecture to production
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Shape the team’s technology, engineering standards and AI strategy
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Collaborate with talented engineers, product leaders and business stakeholders
What You’ll Be Doing
-
Design and build production AI agents and agentic workflows
-
Develop scalable software using Python, TypeScript or JavaScript
-
Integrate LLMs with APIs, databases and enterprise systems
-
Contribute to architecture and technical design
-
Own features across the full SDLC, from design to deployment
-
Build testing, observability and monitoring into AI applications
-
Debug and optimise agent reliability, performance and quality
-
Contribute to CI/CD, Kubernetes and cloud infrastructure
What We’re Looking For
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Proven experience building full-stack software at scale, ideally 1M+ users
-
Commercial experience with AI/ML, LLMs or AI agents
-
Strong Python, TypeScript or JavaScript skills
Salary & Benefits
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Competitive base salary!
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Defined contribution pension scheme + Bonus scheme + more
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Hybrid working model within the Cork office
If you’re looking to expand your career in AI at scale, we’d love to hear from you.
Contact Serena Akbib on +353 1 960 9972 or send your CV to [email protected].
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
You will be assessed on your ability to design, build, and deploy scalable AI agent solutions using Python, TypeScript, or JavaScript. Expect focus on integrating LLMs, architecting production-grade systems, and collaborating across teams to deliver robust, enterprise-ready AI experiences.
- AI agent development·High
- Full-stack engineering·High
- LLM integration·High
- Scalable architecture·High
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review AI Agent and LLM Integration Projects
0–10 minList and outline your most relevant experiences building AI agents and integrating LLMs with APIs or enterprise systems.
Brush Up on Full-stack and Cloud Technologies
10–17 minQuickly review key concepts and recent work using Python, TypeScript, JavaScript, Kubernetes, and cloud platforms.
Prepare End-to-End Ownership Examples
17–24 minSelect 1-2 stories where you owned a feature or project from design through deployment, focusing on outcomes and challenges.
Draft Questions for the Team
24–30 minWrite down thoughtful questions about technical challenges, team culture, and engineering standards to ask during the interview.
Talking points
, 6 itemsDesigning and Building AI Agents
You will be expected to architect and implement agentic workflows that go beyond chatbots, requiring deep understanding of AI agent design and real-world application.
Integrating LLMs with Enterprise Systems
The role requires connecting large language models to APIs, databases, and business processes, so you must demonstrate experience in this integration.
Full-stack Development with Python, TypeScript, or JavaScript
Strong coding skills in these languages are essential for building scalable, production-ready software across the stack.
Cloud Infrastructure and Kubernetes
You will contribute to cloud and Kubernetes infrastructure, making knowledge of deployment, scaling, and orchestration critical.
CI/CD and DevOps Practices
Ownership of the full SDLC, including deployment and monitoring, means you need to be comfortable with CI/CD pipelines and operational best practices.
Testing, Observability, and Monitoring in AI Applications
Building reliable AI solutions at scale requires robust testing and monitoring to ensure quality and performance.
What to research
, 3 itemsAI Agent and LLM Integration
Expect deep questions on your experience designing, building, and integrating AI agents and LLMs with enterprise systems, as this is central to the role.
Full-stack and Cloud Engineering at Scale
Be ready to discuss your ability to build, deploy, and maintain scalable software using Python, TypeScript, JavaScript, Kubernetes, and cloud infrastructure.
End-to-End Feature Ownership
Prepare to demonstrate how you manage features or projects from initial design through production, including collaboration and operational excellence.
Questions to ask
, 6 itemsWhat are the biggest technical challenges the Agentic AI team is currently facing?
Why ask this? Reveals the team's priorities and where your skills can have the most impact.
How does the team approach integrating LLMs with enterprise systems?
Why ask this? Clarifies the technical stack and integration patterns you'll work with.
What does end-to-end ownership look like for engineers on this team?
Why ask this? Helps you understand expectations for autonomy and responsibility.
How is success measured for AI products reaching millions of users?
Why ask this? Shows how impact is tracked and what outcomes matter most.
How does the team ensure reliability and quality in rapidly evolving AI solutions?
Why ask this? Gives insight into testing, monitoring, and operational standards.
What opportunities exist for shaping the team's engineering standards and culture?
Why ask this? Indicates how much influence you'll have in team development.
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