AI Engineer (Databricks)

TL;DR

AI Engineer (Databricks/LLM): Designing and delivering production-grade LLM systems and classical ML solutions with an accent on RAG pipelines, agentic workflows, and distributed workloads. Focus on system-level optimization for latency and cost, architecting scalable GenAI services on Databricks, and translating business needs into production architectures.

Location: Budapest, Hungary (Europe)

Company

A Budapest-based team of 250+ data and tech enthusiasts specializing in data engineering, AI, and analytics for global clients.

What you will 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) and agentic workflows.
• Architect and optimize distributed GenAI and ML workloads on Databricks leveraging Spark and MLflow.
• Implement evaluation frameworks to measure quality, hallucinations, and performance.
• Productionize systems utilizing CI/CD, monitoring, rollback, and versioning.
• Lead technical decisions in client engagements and contribute to pre-sales architecture discussions.

Requirements

• 5+ years of experience in Data Science or a related field.
• Proven experience delivering LLM-based systems and classical ML projects to production.
• Strong hands-on experience with RAG, agents, and open-source LLMs.
• Proficiency in Python, SQL, Databricks, and distributed computing (Spark).
• Experience deploying scalable ML/LLM systems on AWS, Azure, or GCP.
• English: Clear, confident communication required for technical discussions

Culture & Benefits

• Opportunity to work on international projects in New York, the Netherlands, Sweden, or Scotland.
• Exposure to cutting-edge tools and advanced technologies.
• Culture of trust and empowerment, providing space to push professional limits.
• Focus on a healthy work-life balance with minimal unnecessary administration.
• Continuous support through a dedicated mentoring system from the first day.
• Supportive corporate environment based on comradery and mutual respect.