AI Engineer (Europe)

What will you do?
Own the architecture and delivery of production-grade LLM systems and classical ML solutions.
Design, evaluate, and optimize RAG pipelines (retrieval strategy, chunking, indexing, monitoring).
Build scalable, production-grade LLM services and agentic workflows, alongside traditional ML systems where appropriate.
Define architecture trade-offs (LLM vs traditional ML, fine-tuning vs RAG, hosted vs self-managed models), with a strong focus on system-level optimization (latency, cost, scalability, reliability).
Architect and optimize distributed GenAI and ML workloads on Databricks (Spark, MLflow), leveraging deep understanding of the platform ecosystem.
Implement evaluation frameworks to measure quality, hallucination, and performance.
Productionize systems with proper CI/CD, monitoring, rollback, and versioning.
Independently design AI solutions tailored to client problems, translating business needs into scalable architectures.
Lead technical decisions in client engagements and actively contribute to pre-sales architecture discussions.
Mentor team members and define GenAI and ML best practices.
What do you need to apply to this role?
5+ years of experience in Data Science or a related field.
Proven experience delivering LLM-based systems to production (not only PoCs), as well as experience with classical ML projects.
Strong hands-on experience with RAG, agents, and open-source LLMs.
Deep understanding of system-level trade-offs (latency, cost, scaling, reliability), and experience optimizing production systems accordingly.
Strong Python and SQL skills.
Deep hands-on experience with Databricks and distributed computing (Spark), including performance optimization.
Experience deploying scalable ML/LLM systems on AWS, Azure, or GCP.
Ability to independently design end-to-end AI solutions in response to client problems.
Client-facing experience and openness to participate in pre-sales processes.
Clear, confident communication in English in technical discussions.

Employment type
Contract

Work arrangement
Hybrid