Senior AI Engineer - Agentic Systems

About the client

Our customer is the European online car market, serving over 30 million monthly users and present in 18 countries. As part of their project, they are building an internal AI platform and are looking for a Senior AI Engineer with genuine, hands-on experience building agentic AI systems - not just integrating existing tools.

This is a hands-on engineering role for someone who has real depth in both AI system design and AWS platform engineering, and who can move fluidly between the two to build production-grade, agentic solutions.

While this is a hands-on role, you will also influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. Duration is 4-6 months with the possibility of prolongation. Time zone: EU or Canadian time zone

Responsibilities:

• Design, build, and maintain agentic AI systems as part of the AI platform
• Work in depth with AWS to build and operate the underlying platform infrastructure
• Design and implement knowledge graph solutions to support AI reasoning and retrieval (e.g. using AWS Neptune or Neo4j)
• Collaborate with cross-functional teams to align the AI platform with business goals and internal use cases
• Troubleshoot and resolve issues across integrated systems to ensure reliable, end-to-end agentic workflows.

Requirements:

• Real, hands-on experience building agentic AI systems - genuine understanding of how they work, beyond just using existing tools or frameworks off the shelf.
• Strong, in-depth AWS experience - real platform engineering depth, not incidental or side use of AWS.
• Strong Python knowledge
• Deep experience building knowledge graphs, ideally with AWS Neptune or Neo4j - especially valuable for this role.
• Experience with LLMs, prompt engineering, and AI integration patterns.
• Strong troubleshooting skills and a collaborative, team-first mindset.
• English level - upper-intermediate (both verbal and written)

Nice to Have:

• Familiarity with MCP (Model Context Protocol).
• Proficiency in infrastructure as code (e.g. CDK in TypeScript/Node.js) to manage AWS services such as Amazon Bedrock and Agent Core.
• Docker/Kubernetes familiarity.