Senior AI Engineer with semantic web tech

EPAM Systems; Turkey; On-site; TRY 5,941,000 - 8,911,000; Full time

Benefits offered by this job

Continuous upskilling & development

Private health insurance

English courses

Competitive USD compensation

Mentoring programs

2,500+ internal courses

Job summary

EPAM Systems seeks a Senior AI Engineer with deep expertise in semantic web technologies to bridge business and technical teams. You will design and operationalize enterprise semantic foundations, translating domain concepts into ontologies, knowledge graphs, and scalable pipelines.

You will lead ontology governance, automate data quality, and collaborate with Data Architects and AI Engineers to ensure semantic consistency and high data quality across enterprise data products.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.
• 5+ years of combined professional experience in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies.
• Expertise in semantic web technologies (RDF, OWL, SPARQL), along with SKOS and SHACL, ontology development, taxonomy creation, and knowledge graph architecture.
• Proficiency in building enterprise-scale ELT/ETL pipelines and data integration frameworks.
• Familiarity with cloud data platforms (Databricks, Snowflake, Azure, or AWS).
• Advanced coding skills in Python and SQL, alongside graph querying and reasoning capabilities.
• Understanding of modern AI patterns, including RAG architectures, vector databases, and LLM integrations, as well as agentic AI systems.
• Knowledge of metadata management, data quality, and lineage, along with governance principles and semantic versioning.
• Excellent verbal and written communication skills; English at B2 level or higher.

Responsibilities

• Lead workshops and discovery sessions with business and technical stakeholders to elicit, define, and document business entities, relationships, attributes, hierarchies, and competency questions.
• Develop and maintain enterprise ontologies, taxonomies, controlled vocabularies, and semantic models.
• Map source systems and business concepts into canonical semantic representations.
• Design, develop, and maintain scalable ELT/ETL frameworks, graph-loading processes, and semantic transformations supporting structured, semi-structured, and unstructured data.
• Implement and optimize graph databases, semantic layers, and metadata repositories to support RAG, Knowledge Graph, and Agentic AI solutions.
• Establish ontology governance frameworks and manage the business glossary and semantic versioning.
• Automate data quality validation, monitoring, lineage, and observability processes.
• Partner with Data Architects, Solution Architects, Data Stewards, and AI Engineers to ensure semantic consistency and high data quality across data products.

Skills

Semantic web technologies (RDF/OWL/SPR

Ontology development

Knowledge graph architecture

Data engineering / ELT pipelines

Python

SQL

Cloud data platforms (Databricks/Snowfl

Graph databases / reasoning

Communication skills

Education

Bachelor's or Master's degree in CS/IS/Data Science/Engineering

Tools

Databricks

Snowflake

Azure

AWS

Neo4j

Amazon Neptune

Job description

We are seeking a Senior AI Engineer with deep expertise in semantic web technologies to act as the strategic bridge between business stakeholders (Data Governance, Enterprise Architecture, AI/Analytics teams) and technical implementation teams.
In this role, you will design, build, and operationalize enterprise semantic and data foundations, translating complex business terminology, metadata requirements, and domain concepts into structured ontologies, knowledge graphs, and scalable data pipelines that power Analytics, AI, Agentic AI, Knowledge Management, and digital solutions.

Responsibilities

• Lead workshops and discovery sessions with business and technical stakeholders to elicit, define, and document business entities, relationships, attributes, hierarchies, and competency questions
• Develop and maintain enterprise ontologies, taxonomies, controlled vocabularies, and semantic models
• Map source systems and business concepts into canonical semantic representations
• Design, develop, and maintain scalable ELT/ETL frameworks, graph-loading processes, and semantic transformations supporting structured, semi-structured, and unstructured data
• Implement and optimize graph databases, semantic layers, and metadata repositories to directly support RAG (Retrieval-Augmented Generation), Knowledge Graph, and Agentic AI solutions
• Establish ontology governance frameworks and manage the business glossary and semantic versioning
• Automate data quality validation, monitoring, lineage, and observability processes
• Partner with Data Architects, Solution Architects, Data Stewards, and AI Engineers to ensure semantic consistency, discoverability, and high data quality across all enterprise data products

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field
• 5+ years of combined professional experience in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies
• Expertise in semantic web technologies (RDF, OWL, SPARQL), along with SKOS and SHACL, ontology development, taxonomy creation, and knowledge graph architecture
• Proficiency in building enterprise-scale ELT/ETL pipelines and data integration frameworks
• Familiarity with cloud data platforms (Databricks, Snowflake, Azure, or AWS)
• Advanced coding skills in Python and SQL, alongside graph querying and reasoning capabilities
• Understanding of modern AI patterns, including RAG architectures, vector databases, and LLM integrations, as well as agentic AI systems
• Knowledge of metadata management, data quality, and lineage, along with governance principles and semantic versioning
• Exceptional verbal and written communication skills, with the ability to articulate complex semantic and data concepts clearly to diverse technical and non-technical stakeholders
• English proficiency at an Upper-Intermediate level (B2) or higher

Nice to have

• Background in semantic tech (RDF, OWL, SPARQL), SKOS, SHACL, and Knowledge Graphs
• Familiarity with AWS, Neo4j, and Amazon Neptune
• Skills in vector databases, semantic layer platforms, and RAG integrations

We offer

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT
  • Diversity of tasks and projects
  • Assessment center for objective review of competency level
  • Personal development plan
  • Mentoring programs and leadership development
  • Certification and professional development support
  • Access to learning platforms including more than 2,500 internal courses
  • English courses taught by certified teachers
• CORPORATE BENEFITS
  • Extra leave days
  • Referral bonuses
• COMPENSATION PACKAGE
  • Competitive compensation paid in USD
  • Regular salary and performance reviews
• MEDICAL & HEALTHCARE
  • Private health insurance
  • Well-being events
• WORKING ENVIRONMENT
  • Recreation areas and kitchens
  • Tea, coffee and snacks
  • Sports equipment and game consoles
  • IT Equipment
  • Microsoft’s Software Assurance Home Use Program (HUP)

Please note that our Talent Attraction Team reviews applications and CVs submitted in English.
EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.