Senior Applied AI Engineer

Salary: Competitive salary + generous bonus

Location: Dublin City Center

Full-Time, Permanent

What’s in it for you:

Ownership: Build and own production-grade agentic AI systems from design through deployment and ongoing operation

Impact: Deliver AI capabilities used across real client-facing solutions and internal accelerators

Tech: Work hands-on with Agentic AI, advanced RAG, LLMOps, MCP, evaluation frameworks and modern AI engineering tooling

Innovation: Join an AI Innovation & R&D team with the freedom to turn emerging AI research into practical solutions

Environment: Collaborate with experienced AI, data science, backend and delivery teams solving complex real-world problems

You’ll join an AI Innovation & R&D team focused on taking Generative AI and Agentic AI beyond prototypes and into reliable, production-ready systems.

This is a hands-on engineering role where you’ll build agentic workflows, advanced retrieval systems and the backend services needed to run them at scale.

You’ll own AI features end to end — from architecture and implementation through evaluation, deployment, monitoring and continuous improvement.

The focus is simple: build AI systems that actually work in production.

The Role:

This is a Senior Applied AI Engineering role focused on building and productionising Generative AI and Agentic AI capabilities.

You’ll design and develop production-grade agents, retrieval systems and AI-powered backend services while helping establish repeatable approaches to evaluation, observability and operational reliability.

You’ll work closely with data science, backend engineering and delivery teams to turn complex business problems into scalable AI solutions.

What You’ll Own:

• Build and own production-grade AI agent systems end to end
• Design stateful and durable agentic workflows
• Develop advanced retrieval and grounding systems
• Build secure integrations between AI agents and internal/external tools
• Create evaluation frameworks that measure AI quality and reliability
• Implement monitoring and observability across AI workflows
• Optimise AI systems for quality, latency and cost
• Build reusable AI components and accelerators
• Help take emerging Agentic AI techniques from research into production

What You’ll Be Doing:

Agentic AI & Orchestration

Design and build production-grade AI agents with planning, tool use, memory and human-in-the-loop workflows.

Retrieval & Evaluation

Build advanced RAG and retrieval systems using embeddings, vector databases and reranking, alongside evaluation frameworks to measure quality and reliability.

AI Tooling & MCP

Develop secure integrations between AI agents, internal services and external APIs using MCP and modern agent tooling.

Backend & Production Engineering

Build scalable Python services and APIs, deploying AI applications using Docker, Kubernetes, CI/CD and cloud platforms.

LLMOps & Performance

Monitor and optimise AI systems across reliability, cost, latency and quality.

Innovation

Explore emerging Agentic AI technologies and turn the most promising approaches into practical, production-ready solutions.

What You’ll Need:

• Around 4–7 years’ experience across software engineering, applied ML or applied AI
• Strong hands-on Python engineering skills
• Experience building and shipping LLM-powered applications
• Practical experience with agentic AI frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI or similar
• Understanding of agent planning, tool use and multi-agent systems
• Hands-on experience with embeddings and vector databases
• Experience with technologies such as Milvus, Pinecone, Weaviate, Chroma or FAISS
• Understanding of retrieval tuning, RAG and grounding techniques
• Experience with modern software engineering practices including testing, code reviews and version control
• Understanding of microservices and event-driven architectures
• Experience deploying applications to AWS, Azure or GCP
• Experience with containerisation and CI/CD
• A strong production mindset around testing, monitoring, governance and operational readiness for AI applications

Nice to Have:

• Knowledge graphs and structured retrieval
• Complex task decomposition
• Advanced evaluation methodologies for agentic systems
• Synthetic data generation and auto-labelling
• Data-centric approaches to building evaluation datasets
• Experience with AI development tools such as Cursor, Windsurf, Replit, GitHub Copilot, Claude Code or Codex
• Experience supporting client-facing delivery teams
• Experience building reusable AI accelerators used across multiple projects

What Success Looks Like:

You’ll ship agentic AI and retrieval components that integrate cleanly into larger enterprise solutions.

Your work will deliver measurable improvements in AI quality, reliability and delivery speed.

You’ll establish repeatable evaluation and monitoring practices that reduce regressions and allow teams to iterate safely.

You’ll take genuine ownership of AI feature delivery while collaborating with backend and platform specialists on deeper infrastructure.

About the Company:

You’ll be joining a global Data and AI organisation working with leading enterprises across industries including insurance, healthcare, banking and financial services, media and retail.

With a significant international presence, the business is investing heavily in AI innovation and building Generative AI and Agentic AI capabilities designed to solve complex, real-world enterprise problems.

You’ll be part of an AI Innovation & R&D team, working at the point where emerging AI technology becomes production software.

Interested?:

If you’re interested in hearing more please feel free to hit apply or fire me on a copy of your cv at [email protected]