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Graphwise

Data Engineer for AI

Sofia, Sofia

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hirly's read of this role

Role family
Data & ML
Seniority
Mid level
Country
BG
Work mode
On-site / unstated
First seen by hirly
1 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

At Graphwise, we help enterprises transform fragmented data into connected, intelligent systems using Knowledge Graphs, semantic technologies, and modern AI architectures.

About the role

We’re looking for a strong candidate with experience in data engineering and an interest in AI systems, data modeling, and large-scale information architectures. You don’t need to be a semantic technologies expert already - what matters most is solid engineering thinking, curiosity, and the ability to work with complex data problems.

Main Responsibilities:

Design and build robust data pipelines for structured and unstructured data

Integrate and harmonize data from multiple enterprise systems

Work on AI-oriented retrieval and context architectures, including RAG and GraphRAG patterns

Build workflows for extracting structured information from documents and text

Contribute to scalable backend and data processing systems

Collaborate with technical and business stakeholders to solve complex information challenges

Explore and adopt modern AI, NLP, and data engineering technologies

Must-haves:

Strong software engineering fundamentals

Professional experience with Python, Java, or Scala

Experience building backend systems or data pipelines

Solid understanding of data modeling and ETL processes

Familiarity with modern AI concepts such as: LLMs, RAG, vector databases, embeddings, or NLP workflows

Experience with Git, CI/CD, and collaborative engineering practices

Strong analytical and problem-solving skills

Good communication skills in English

Curiosity and willingness to learn new domains and technologies

Nice-to-haves:

Knowledge Graphs or graph databases

Semantic technologies such as RDF, OWL, SHACL, or SPARQL

Ontology or taxonomy modeling

NLP Basics: Basic understanding of Knowledge Extraction, specifically identifying and linking entities within text.

NLP tooling such as SpaCy or similar libraries

GraphRAG implementations

Cloud platforms and distributed systems

What you'll get

A friendly and professional international team within a fast-growing AI company.

The opportunity to work on technically challenging enterprise systems used by leading global organizations.

Exposure to cutting-edge technologies in AI, knowledge graphs, semantic technologies, and cloud-native architectures.

A collaborative engineering culture focused on learning, innovation, and continuous improvement.

A workplace committed to sustainability and responsible business practices.

An international environment where English is the primary working language and more than 65% of colleagues come from across the globe.

Flexible working hours and benefits that support a healthy work-life balance.

Clear opportunities for professional growth through internal and external training, knowledge sharing, and hands-on experience with modern technologies.

And, of course, free tea, coffee, fresh fruit, and snacks.

Graphwise is an equal opportunity employer. We do not and will not discriminate on the basis of age, disability, sex, race, religion or belief, gender reassignment, marriage or civil partnership status, pregnancy or maternity, or sexual orientation. All employment decisions, including recruitment, hiring, development, promotion, compensation, and other terms and conditions of employment, are based on merit, qualifications, performance, and business needs. We are dedicated to providing an environment free from discrimination, harassment, and bias, and we welcome applications from all qualified candidates.

Original posting on Graphwise's site ↗

Listed on hirly, a job board. hirly is not the employer: Graphwise is hiring for this role.

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