Senior Ontology and Knowledge Graph Engineer (m/f/d)

Siemens AG; Amadora; Hybrid; EUR 80,000 - 110,000; Full time

Benefits offered by this job

Hybrid model

Home office budget

Health insurance

Mental health support

Learning platforms

Mentoring & development

Sustainability & volunteering

Partner discounts

Shuttle service

Job summary

Siemens AG is seeking a Senior Ontology and Knowledge Graph Engineer to design enterprise ontologies, build and govern the Enterprise Knowledge Graph, and drive AI readiness across data pipelines and semantic layers.

You will collaborate with AI/ data teams to optimize semantic contexts for LLMs and enable RAG-based use cases within Siemens’ GBS environment. A strong background in RDF/OWL/SKOS and Python is essential.

Qualifications

• 5+ years hands-on experience in Ontology Engineering or semantic data modeling.
• Proficient in RDF, OWL, SKOS and applying semantic standards in enterprise contexts.
• Strong Python skills for data pipelines and integrations.
• Experience with LLMs and AI tooling is highly desirable.
• Familiarity with Finance/HR/Sales domains is a plus.

Responsibilities

• Design and maintain enterprise ontologies and semantic schemas (OWL, RDF, SKOS).
• Architect and implement the Enterprise Knowledge Graph, defining entities, relationships, and semantic layers.
• Build scalable data ingestion pipelines from SAP, Workday, and other platforms into the knowledge graph.
• Collaborate with Data and AI Engineers to design semantic context for LLMs and optimize prompts.
• Enable knowledge-centric AI with RAG architectures and vector databases.
• Define semantic standards and governance across the AI and analytics ecosystem.
• Mentor engineers on ontology engineering, graph thinking, and semantic technologies.
• Ensure data governance and security standards while driving innovation in semantic AI.

Skills

Ontology Engineering

SPARQL

Cypher

Python

RDF/OWL/SKOS

LLM Integration

Vector Databases

RAG architectures

Data Pipelines

Enterprise Knowledge

Education

Bachelor's degree in Computer Science, Information Science, or a related field

Master's degree in Computer Science or related field

PhD in a relevant field

Tools

SAP

Workday

Job description

Senior Ontology and Knowledge Graph Engineer (m/f/d)

525408

16-Oct-2026

Global Business Services

Information Technology

Siemens Global Business Services (GBS) enables Siemens units worldwide and external customers to accelerate their business transformation into a sustainable and digital future.

Our portfolio comprises services driven by expertise and the latest technology – with a strong focus on innovation and digitalization in areas like Finances, Business Administration, Human Resources, Procurement, Sales and After-Sales.

In our GBS Western Europe and Africa Hub we are already more than 1500 connected people, from over 50 different nationalities spread across 14 countries. If you value diversity and innovation, you will feel right at home here!

Discover our purpose, culture, and what makes GBS unique!

Are you ready to be part of the change? Come join us!

The GBS Digital Solutions (DS) Enterprise Architecture team, part of Governance, Cybersecurity & Integration (GCI), sets the architecture direction for GBS. We enable, facilitate and govern, working with the business lines and delivery teams rather than apart from them. Our goal is simple: decide faster, and apply the right technology to each use case.

What role will you play?

• Ontology & Semantic Design: Design and maintain enterprise grade ontologies and semantic schemas (OWL, RDF, SKOS) across shared services domains such as AP, Hire to Retire, Sales, and Delivery.
• Enterprise Knowledge Graph: Architect and implement the Enterprise Knowledge Graph, defining entities, relationships, and semantic layers to unify structured and unstructured enterprise data.
• Data Integration & Pipelines: Build and manage scalable data ingestion pipelines integrating data from systems such as SAP, Workday, and other enterprise platforms into the knowledge graph.
• Context Engineering for AI: Collaborate with Data and AI Engineers to design semantic context for LLMs, optimizing prompt inputs to improve reasoning, accuracy, and explainability.
• RAG & AI Enablement: Enable knowledge centric AI use cases by integrating knowledge graphs with LLMs, vector databases, and Retrieval Augmented Generation (RAG) architectures.
• Semantic Standards & Governance: Define and enforce semantic modeling standards, best practices, and governance policies across the AI and analytics ecosystem.
• Collaboration & Mentorship: Partner with cross functional teams and mentor engineers on ontology engineering, graph based thinking, and semantic technologies.
• Quality, Security & Innovation: Ensure compliance with data governance and security standards while driving continuous improvement through emerging semantic and AI technologies.

What do you bring?

• Educational Background: Bachelor's degree in Computer Science, Information Science, or a related field with 5+ years of relevant experience; OR Master's degree with 4+ years of relevant experience; OR PhD with 2+ years of relevant experience.
• Ontology & Knowledge Engineering Experience: Minimum 5+ years of hands on experience in Ontology Engineering, Knowledge Representation, or Semantic Data Modeling in enterprise environments.
• Technical Stack:
• Graph Technologies: High proficiency in graph query languages (e.g., SPARQL, Cypher).
• Programming: Solid software engineering skills with strong proficiency in Python, including building data pipelines and integrations.
• Semantic Web Standards: Deep practical experience with RDF, OWL, and SKOS, and applying semantic standards to real world business domains.
• AI & LLM Integration: Experience working with LLMs, Vector Databases, and Retrieval Augmented Generation (RAG) architectures is highly desirable.
• Enterprise & Domain Knowledge: Familiarity with shared services domains such as Finance (Accounts Payable), HR (Hire to Retire), or Sales and Delivery operations is a strong advantage.
• Analytical & Collaboration Skills: Strong analytical mindset with the ability to collaborate effectively across data, AI, and business teams to translate domain knowledge into semantic models.

What We Offer:

• Belong & Innovate: Work in diverse teams where every idea matters and innovation grows through collaboration and trust.
• Flexibility that Works: Hybrid model, flexible hours, and a home office budget - because balance fuels performance.
• Health & Well-being: Comprehensive health insurance, mental health support, and active sports communities to keep you feeling your best.
• Grow Without Limits: Access world-class learning platforms, mentoring, and continuous development opportunities.
• Purpose & Perks: Contribute to sustainability and volunteer initiatives, enjoy partner discounts, and take advantage of our convenient shuttle service.

Create a better #TomorrowWithUs #Siemens

Siemens is deeply committed to fostering a diverse and inclusive environment. We are proud to be an equal opportunity employer and strongly encourage applications from a wide array of talented individuals!