Senior AI Engineer Senior ML Engineer

Pure Storage

Prague, Czech Republic

Full Time

Posted April 30, 2026

Not Specified

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Job Description

A Senior Applied AI Engineer responsible for designing, developing, and deploying production-grade AI systems that analyze large-scale unstructured data using knowledge graphs, LLMs, and machine learning models to extract meaningful insights for enterprise data discovery, classification, and governance.

Key Responsibilities

Design, build, and deploy graph-based AI solutions using knowledge graphs, LLMs, and ML models on large-scale unstructured data
Develop and maintain data pipelines for extracting, transforming, and enriching entity relationships into knowledge graphs
Integrate LLMs and ML models into text processing workflows for classification, embedding generation, document similarity, and semantic analysis
Deploy, monitor, and optimize graph and vector databases to support retrieval, reasoning, and analytics
Ensure the reliability and continuous improvement of ML systems in production environments
Make architectural and technical decisions for applied AI and graph intelligence solutions

Requirements

Proven experience in developing and deploying to production knowledge graphs in a real business scenario.
Strong hands-on background in developing text-based ML and LLM systems, including prompt context engineering, optimized for production environments.
Strong proficiency in Python programming language.
Experience with ML knowledge graph frameworks and tools such as Neo4j, NetworkX, Node2Vec, and SentenceTransformers, with the ability to select the right tool for the problem at hand.
Ability to apply appropriate graph algorithms and design choices for problem solving, including relationship and ontology modeling, feature definition, and supervised vs unsupervised graph analytics.
Ability to design clean, modular, and testable ML code in a collaborative environment.
Experience with MLOps practices, including building production-grade Docker images and developing AI solutions designed for integration into production systems.
Experience collaborating with software engineers, product managers, and business stakeholders.
Strong communication skills and the ability to explain ML concepts and system behavior clearly.