Senior AI Engineer: Production-Grade Systems & Agentic AI

Adecco; Dublin; On-site; EUR 120,000 - 170,000; Full time

Job summary

Adecco in Ireland is seeking a Senior Python / AI Engineer to join a high-performing engineering team working on large-scale, high-volume systems. You will contribute from day one, blending strong software fundamentals with modern AI expertise in system integration and production-grade AI at scale.

You will design agentic AI workflows, apply RAG architectures, and implement governance and reliability techniques to ensure robust, scalable deployments in a fast-evolving AI landscape.

Qualifications

• 8–10+ years of software engineering experience.
• Experience designing and building large-scale, high-volume systems.
• Proven experience building and deploying AI-powered applications in production.
• Hands-on experience designing agentic AI workflows.
• Strong understanding of RAG and modern AI architectures.
• Experience with AI guardrails, governance, policies and reliability techniques.

Responsibilities

• Push the boundaries of what can be built and turn emerging AI capabilities into reliable production systems.
• Contribute from day one in a complex environment and raise the engineering bar with technical expertise.
• Lead system integration and orchestration in AI workflows to ensure scalable deployments.
• Collaborate with cross-functional teams to maintain high engineering standards and quality.

Skills

Software engineering

AI in production

System integration

Agentic AI

RAG architectures

Governance & guardrails

Multi-agent systems

Production-grade software

AI orchestration

Tools

Python

CI/CD

Cloud platforms

Job description

Adecco in Ireland is seeking a Senior Python / AI Engineer to join a high-performing engineering team working on large-scale, high-volume systems. You will contribute from day one, blending strong software fundamentals with modern AI expertise in system integration and production-grade AI at scale.

You will design agentic AI workflows, apply RAG architectures, and implement governance and reliability techniques to ensure robust, scalable deployments in a fast-evolving AI landscape.