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Principal Consultant – Semantic Data & AI Engineering

Pay
USD 146,000–183,000/yearAnnual period assumed — pay source
US Pay Range $146,000—$183,000 USD
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Work setting
Not stated
Employment
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What you’ll work on

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

From the employer’s 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. 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.

What you’ll bring

All qualifications

Preferred experience

  • Experience with data governance, metadata management, entity resolution, master data, responsible AI, model risk, or regulatory reporting is advantageous.
Qualification wording
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.

Benefits in the posting

Full benefits wording
  • Medical, Dental and Vision.
  • 401k match.
  • Maternity and paternity leave and dependent care.
  • Tuition reimbursement and wellness reimbursement.
  • Working Advantage (discounted marketplace), HSA, FSA, and commuter benefits.
  • Inclusion at Capco
  • US Pay Range

From the employer’s posting.

Apply at Capco

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Status in our records
Live
First seen by us
Aug 17, 202679 days ago
Recorded sightings
307
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Time since we first saw it

Day 79

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

Capco is hiring

77 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 3% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • AWS
  • Azure
  • BigQuery
  • Databricks
  • Neo4j
  • Redshift
  • Snowflake
  • GCP
Where the posting names them
- 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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About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

Principal Consultant – Semantic Data & AI Engineering

Capco | Data & Analytics | New York, NY

About the Role

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.

What You’ll Do

  • Design and implement enterprise knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products.
  • Translate business concepts, policies, documents, data models, and subject-matter expertise into governed, 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 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.
  • 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.
  • Work with data engineers to implement batch, streaming, and API-driven pipelines using modern cloud and data platforms.
  • Define semantic-data quality controls, provenance, lineage, confidence scoring, versioning, and governance processes.
  • Evaluate graph databases, vector databases, data platforms, AI frameworks, and cloud services based on client requirements.
  • Lead technical workshops, architecture decisions, prototypes, and production implementations.
  • Mentor team members and create reusable patterns, accelerators, and reference architectures for Capco’s Graph, Semantics & AI practice.
  • Support proposals, solution estimates, client presentations, and the development of new consulting offerings.

What You’ll Bring

  • Eight or more years of experience in data engineering, software engineering, artificial intelligence, analytics, enterprise architecture, or a related field.
  • At least four years of hands-on experience with knowledge graphs, semantic technologies, graph databases, or semantic-data integration.
  • 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.
  • Experience developing data pipelines, APIs, transformations, automated tests, and production integrations.
  • Working knowledge of NLP, machine learning, embeddings, vector search, semantic search, RAG, GraphRAG, or LLM-based applications.
  • 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.
  • Experience with Git, CI/CD, automated testing, containers, Agile delivery, and production-support practices.
  • Ability to communicate technical concepts clearly to business stakeholders, architects, engineers, data scientists, and executives.
  • Demonstrated ability to operate across multiple roles, learn new technologies quickly, and take ownership from initial discovery through production delivery.

Preferred Experience

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.

 

Why Join Capco

  • Deliver high-impact technology solutions for Tier 1 financial institutions.
  • Work in a collaborative, flat, and entrepreneurial consulting culture.
  • Access continuous learning, training, and industry certifications.
  • Be part of a team shaping the future of digital financial services.
  • Help shape the future of digital transformation across FS & Energy.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Benefits

  • Medical, Dental and Vision.
  • 401k match.
  • Maternity and paternity leave and dependent care.
  • Tuition reimbursement and wellness reimbursement.
  • Working Advantage (discounted marketplace), HSA, FSA, and commuter benefits.

Inclusion at Capco

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
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Pay
US Pay Range $146,000—$183,000 USD
Location & working pattern

US - New York

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