Lead AI Engineer with semantic web tech

EPAM Systems Inc; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

EPAM Systems seeks a Lead AI Engineer to shape the enterprise semantic and knowledge engineering program. You will define the vision, architect ontologies, and drive adoption of semantic data foundations across analytics, AI, and digital solutions.

You will mentor engineers, set standards, and guide teams through workshops with business and tech stakeholders. Strong expertise in RDF/OWL/SPARQL and data governance is required, with a focus on enterprise-scale implementations.

Qualifications

• Bachelor's or Master's in CS/IS/Data Science/Engineering.
• 7+ years in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies.
• 1+ year leading technical teams or initiatives.
• Deep hands-on expertise in semantic web techs (RDF, OWL, SPARQL).
• Experience designing enterprise ELT/ETL pipelines and data integration.
• Strong cloud platform experience (Databricks, Snowflake, Azure, AWS).
• Proficient in Python and SQL; capable in graph querying and reasoning.
• Understanding of RAG architectures, vector databases, and agentic AI systems.
• Excellent communication and leadership for executive-level collaboration.

Responsibilities

• Define strategic roadmap for enterprise semantic and knowledge engineering.
• Lead and mentor engineers to foster technical excellence and growth.
• Document business entities, relationships, and domain concepts with stakeholders.
• Architect ontologies, taxonomies, and semantic models across domains.
• Define standards for mapping concepts into canonical semantic representations.
• Drive ELT/ETL, graph loading, and semantic transformations for diverse data types.
• Guide graph databases, semantic layers, and metadata repositories for AI solutions.
• Establish ontology governance and semantic versioning at enterprise scale.
• Collaborate with architects and data stewards to ensure data quality and discoverability.
• Represent the organization in cross-functional technical forums.

Skills

Semantic Web Technologies

Leadership

Knowledge Graph Architecture

Python

SQL

Communication

AI/ML Patterns

Data Governance Collaboration

Education

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

Tools

Databricks

Snowflake

Azure

AWS

Neo4j

Amazon Neptune

RDF

OWL

SPARQL

SKOS

SHACL

Job description

We are seeking a Lead 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 define the vision, architect, and drive the enterprise-wide adoption of 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. As a technical leader, you will mentor engineers, set standards, and shape the strategic direction of our semantic and knowledge engineering practice.

Responsibilities

• Define the strategic roadmap for enterprise semantic and knowledge engineering initiatives, aligning them with long-term business and technology goals
• Lead and mentor a team of engineers, fostering technical excellence, knowledge sharing, and professional growth
• Lead workshops and discovery sessions with senior business and technical stakeholders to elicit, define, and document business entities, relationships, attributes, hierarchies, and competency questions
• Architect and own enterprise ontologies, taxonomies, controlled vocabularies, and semantic models across multiple domains
• Establish standards for mapping source systems and business concepts into canonical semantic representations
• Define architectural blueprints for scalable ELT/ETL frameworks, graph-loading processes, and semantic transformations supporting structured, semi-structured, and unstructured data
• Drive the design and evolution of graph databases, semantic layers, and metadata repositories to directly support RAG (Retrieval-Augmented Generation), Knowledge Graph, and Agentic AI solutions
• Establish and chair ontology governance frameworks, business glossary stewardship, and semantic versioning policies at the enterprise level
• Define best practices for automated 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
• Represent the organization in cross-functional forums and influence enterprise-wide technical decisions

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field
• 7+ years of combined professional experience in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies
• 1+ years of proven experience leading technical teams or initiatives
• Deep, hands-on expertise in semantic web technologies (RDF, OWL, SPARQL), along with SKOS and SHACL, ontology development, taxonomy creation, and knowledge graph architecture at enterprise scale
• Proven track record of designing and delivering enterprise-scale ELT/ETL pipelines and data integration frameworks
• Strong experience with cloud data platforms (Databricks, Snowflake, Azure, or AWS)
• Advanced coding skills in Python and SQL, alongside graph querying and reasoning capabilities
• Strategic understanding of modern AI patterns, including RAG architectures, vector databases, and LLM integrations, as well as agentic AI systems, with the ability to guide architectural decisions
• Comprehensive knowledge of metadata management, data quality, and lineage, along with governance principles and semantic versioning
• Demonstrated leadership and mentoring skills, with a history of guiding senior engineers and shaping technical culture
• Exceptional verbal and written communication skills, with the ability to articulate complex semantic and data concepts clearly to executive-level, technical, and non-technical audiences
• English proficiency at an Upper-Intermediate level (B2) or higher

Nice to have

• Experience representing organizations in industry forums, publishing thought leadership, or contributing to open-source semantic technology communities
• Advanced background in semantic tech (RDF, OWL, SPARQL), SKOS, SHACL, and Knowledge Graphs
• Familiarity with AWS, Neo4j, and Amazon Neptune
• Deep expertise in vector databases, semantic layer platforms, and RAG integrations
• Experience defining enterprise architecture standards and governance frameworks across multiple business units