Pay
Lower than most similar jobs
$146K–$183K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
US - New York
Live, first seen by us 79 days agoUS Pay Range $146,000—$183,000 USDRead the full posting
Capco is seeking a hands-on Principal Consultant to design and build semantic data solutions that make enterprise data usable by artificial intelligence, machine learning, analytics, and business applications.
This role is designed for a versatile technical leader who can move across knowledge-graph engineering, AI solution development, data modeling, and data-pipeline delivery.
Design and implement knowledge graphs, semantic layers, and ontologies
Build semantic data pipelines that acquire, transform, and load data
Integrate knowledge graphs with generative AI, RAG, and semantic search
Support NLP and document-intelligence use cases like entity extraction
Develop Python or Java services, transformations, APIs, and validation routines
Capco is seeking a hands-on Principal Consultant to design and build semantic data solutions that make enterprise data usable by artificial intelligence, machine learning, analytics, and business applications.
This role is designed for a versatile technical leader who can move across knowledge-graph engineering, AI solution development, data modeling, and data-pipeline delivery. The successful candidate will help clients connect structured and unstructured information, create machine-understandable representations of business knowledge, and provide trusted context for AI applications.
Design and implement enterprise knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products.
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 machine-learning solutions, including generative AI, retrieval-augmented generation, GraphRAG, semantic search, and intelligent agents.
Support NLP and document-intelligence use cases such as entity extraction, entity linking, relationship extraction, classification, natural language inference, and knowledge extraction.
Develop Python- or Java-based services, data transformations, APIs, validation routines, and integration components.
Financial-services or other regulated-industry experience is strongly preferred. Experience with data governance, metadata management, entity resolution, master data, responsible AI, model risk, or regulatory reporting is advantageous.
From the employer’s posting.
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Lower than most similar jobs
$146K–$183K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Day 79
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From 4,296 similar postings that came down. Coming down is not always a hire.
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- Combine graph traversal, vector search, metadata, rules, and model-generated results to improve AI accuracy, grounding, explainability, and traceability. - Develop Python- or Java-based services, data transformations, APIs, validation routines, and integration components. - Work with data scientists and AI engineers to prepare training, retrieval, evaluation, and inference data.
- Experience with one or more graph platforms such as Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, TypeDB, or equivalent technologies. - Strong programming skills in Python, Java, or a comparable enterprise language. - Experience developing data pipelines, APIs, transformations, automated tests, and production integrations.
- Experience connecting structured data with unstructured content such as policies, contracts, research, communications, or operational documents. - Familiarity with cloud and modern data platforms such as Microsoft Azure, AWS, Google Cloud, Microsoft Fabric, Databricks, Snowflake, BigQuery, or Redshift. - Understanding of relational, graph, document, vector, and lakehouse architectures and when to use each.
- Strong knowledge of RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, Turtle, or related standards. - Experience with one or more graph platforms such as Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, TypeDB, or equivalent technologies. - Strong programming skills in Python, Java, or a comparable enterprise language.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Capco | Data & Analytics | New York, NY
Capco is seeking a hands-on Principal Consultant to design and build semantic data solutions that make enterprise data usable by artificial intelligence, machine learning, analytics, and business applications.
This role is designed for a versatile technical leader who can move across knowledge-graph engineering, AI solution development, data modeling, and data-pipeline delivery. The successful candidate will help clients connect structured and unstructured information, create machine-understandable representations of business knowledge, and provide trusted context for AI applications.
You will work across multiple project roles depending on client needs—serving as a semantic architect, knowledge-graph engineer, AI engineer, data engineer, technical lead, or client advisor. This is not a research-only or ontology-only position. The role requires someone who can translate business requirements into practical solutions and contribute directly to architecture, code, data pipelines, testing, and production delivery.
Financial-services or other regulated-industry experience is strongly preferred. Experience with data governance, metadata management, entity resolution, master data, responsible AI, model risk, or regulatory reporting is advantageous.
Relevant cloud, data-engineering, AI/ML, Agile, or graph-technology certifications are a plus.
We offer a competitive, people-first benefits package designed to support every aspect of your life:
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.
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US Pay Range $146,000—$183,000 USD
US - New York
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