Principal Consultant – Semantic Data & AI Engineering

About the role

Capco is looking for a hands-on Principal Consultant to design and build semantic data solutions that make enterprise data usable by AI, machine learning, analytics and business applications. The role spans knowledge-graph engineering, AI solution development, data modeling and data-pipeline delivery, and the consultant acts as semantic architect, knowledge-graph engineer, AI engineer, data engineer, technical lead or client advisor depending on client needs.

Key responsibilities

• Design and implement knowledge graphs, semantic layers, ontologies, taxonomies and graph-based data products.
• Turn business concepts, policies, documents and subject-matter expertise into machine-readable knowledge models.
• Build semantic data pipelines that acquire, transform, map, validate, enrich and load data from databases, APIs, files, documents, events and cloud platforms.
• Integrate knowledge graphs with AI and ML solutions such as generative AI, RAG, GraphRAG, semantic search and intelligent agents.
• Support NLP and document-intelligence use cases like entity extraction, entity linking, relationship extraction, classification and knowledge extraction.
• Develop Python- or Java-based services, data transformations, APIs, validation routines and integration components.
• Prepare training, retrieval, evaluation and inference data for data scientists, and build batch, streaming and API-driven pipelines with data engineers.
• Define quality controls, provenance, lineage, confidence scoring, versioning and governance, and evaluate graph, vector and data platforms.
• Lead workshops, architecture decisions, prototypes and production implementations, mentor team members and support proposals and client presentations.

Required profile

• 8+ years of experience in data engineering, software engineering, AI, analytics, enterprise architecture or a related field.
• 4+ years of hands-on experience with knowledge graphs, semantic technologies, graph databases or semantic-data integration.
• Experience connecting structured data with unstructured content such as policies, contracts, research and operational documents.
• Ability to communicate technical concepts to business stakeholders, architects, engineers, data scientists and executives, and to take ownership from discovery through production delivery.
• Preferred: financial-services or regulated-industry experience, and experience with data governance, metadata management, entity resolution, master data, responsible AI, model risk or regulatory reporting.

Required skills

• RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, Turtle or related standards.
• Graph platforms such as Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, TypeDB or equivalents.
• Python or Java, and experience building data pipelines, APIs, transformations, automated tests and production integrations.
• NLP, embeddings, vector search, RAG, GraphRAG and LLM-based applications.
• Cloud platforms such as Azure, AWS, Google Cloud, Microsoft Fabric, Databricks, Snowflake, BigQuery or Redshift.
• Git, CI/CD, containers, Agile delivery and production-support practices.

What we offer

• Pay range of $146,000-$183,000 USD.
• Medical, dental and vision coverage, 401k match, maternity and paternity leave and dependent care.
• Tuition and wellness reimbursement, Working Advantage, HSA, FSA and commuter benefits.
• A collaborative, flat consulting culture with continuous learning and certifications.