Asks for

The ad says“Experience with MLOps practices, building production-grade Docker images, and development of AI solutions designed for integration into production systems”
The ad says“Ability to apply the appropriate graph algorithms and design choices for problem solving, including relationship and ontology modelling, feature definition, supervised vs unsupervised graph analytics”
The ad says“Proven experience in developing and deploying to production knowledge graphs in a real business scenario”
The ad says“Strong hands-on background in developing text-based ML and LLM systems, including prompt context engineering, optimized for production environments”
The ad says“Strong hands-on background in developing text-based ML and LLM systems, including prompt context engineering, optimized for production environments”
The ad says“Experience with MLOps practices, building production-grade Docker images, and development of AI solutions designed for integration into production systems”
The ad says“Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand”
The ad says“Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand”
The ad says“Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand”
The ad says“Ability to apply the appropriate graph algorithms and design choices for problem solving, including relationship and ontology modelling, feature definition, supervised vs unsupervised graph analytics”
The ad says“Strong hands-on background in developing text-based ML and LLM systems, including prompt context engineering, optimized for production environments”
The ad says“Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand”
The ad says“Ability to apply the appropriate graph algorithms and design choices for problem solving, including relationship and ontology modelling, feature definition, supervised vs unsupervised graph analytics”
The ad says“Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand”

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.

This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.

THE ROLE

Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance.

This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements.

WHAT YOU'LL DO

Design, build, and deploy graph-based AI solutions, combining knowledge graphs, LLMs, and ML models applied to large-scale unstructured data
Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs
Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis
Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics
Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure
Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration
Drive architectural decisions and technical direction for applied AI and graph intelligence solutions
We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

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, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand
Ability to apply the appropriate graph algorithms and design choices for problem solving, including relationship and ontology modelling, feature definition, supervised vs unsupervised graph analytics
Ability to design clean, modular, and testable ML code in a collaborative environment
Experience with MLOps practices, building production-grade Docker images, and development of AI solutions designed for integration into production systems
Experience collaborating with software engineers, product managers, and business stakeholders
Strong communication skills and ability to explain ML concepts and system behavior clearly

#LI-ONSITE

WHAT YOU CAN EXPECT FROM US:

Innovation: We celebrate those who think critically, like a challenge, and aspire to be trailblazers.
Growth: We give you the space and support to grow along with us and to contribute to something meaningful. We have been named Fortune's Best Workplaces in Technology™, Fortune's Best Workplaces in the Bay Area™, and certified as a Great Place to Work®!
Team: We build each other up and set aside ego for the greater good.

And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources, and company-sponsored team events. Check out http://benefits.everpuredata.com/ for more information.

ACCOMMODATIONS AND ACCESSIBILITY:

Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this, contact us at TA-Ops@purestorage.com if you’re invited to an interview.

OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM:

We’re forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isn’t just accepted but embraced. That’s why we are committed to fostering the growth and development of every person, cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership.

Everpure is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire.

Join us and bring your best.

Bring your bold.

Pure and simple.