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Knowledge Engineering Jobs in New York (NOW HIRING)

Squirro

Knowledge Graph Engineer

New York, NY · Remote

Collaborate with product, engineering, and delivery teams to translate customer requirements into ... In-depth knowledge of semantic web standards (RDF, SKOS, OWL, SPARQL) * Familiarity with graph ...

Allergan

Principal Engineer, Facilities

Branchburg, NJ · On-site

$90 - $120/hr

An engineering professional who, working with little or no supervision, applies scientific knowledge, engineering knowledge, mathematics, and ingenuity to complete assignments related to a specific ...

AbbVie

Principal Engineer, Facilities

Branchburg, NJ · On-site

An engineering professional who, working with little or no supervision, applies scientific knowledge, engineering knowledge, mathematics, and ingenuity to complete assignments related to a specific ...

Point72

Data Engineer, Knowledge Graph

New York, NY · On-site

$125K - $150K/yr

Define and implement best practices for knowledge graph development, implementation, and ... We value your proven ability to build and lead engineering teams through complex technical ...

AbbVie

Principal Engineer, Facilities

Branchburg, NJ · On-site

An engineering professional who, working with little or no supervision, applies scientific knowledge, engineering knowledge, mathematics, and ingenuity to complete assignments related to a specific ...

Point72

Data Engineer, Knowledge Graph

New York, NY · On-site

$125K - $150K/yr

Define and implement best practices for knowledge graph development, implementation, and ... We value your proven ability to build and lead engineering teams through complex technical ...

Point72

Data Engineer, Knowledge Graph

Manhattan, NY · On-site

$126K - $151K/yr

Define and implement best practices for knowledge graph development, implementation, and ... We value your proven ability to build and lead engineering teams through complex technical ...

AbbVie

Principal Engineer, Facilities

Branchburg, NJ · On-site

$109K/yr

An engineering professional who, working with little or no supervision, applies scientific knowledge, engineering knowledge, mathematics, and ingenuity to complete assignments related to a specific ...

AbbVie

Process Engineer II (IQ,OQ,PQ)

Branchburg, NJ · On-site

The primary job function of this position is to provide technical support to cross-functional teams working with little or no supervision, apply project management knowledge, engineering and product ...

AbbVie

Process Engineer II (IQ,OQ,PQ)

Branchburg, NJ · On-site

The primary job function of this position is to provide technical support to cross-functional teams working with little or no supervision, apply project management knowledge, engineering and product ...

AbbVie

Process Engineer II (IQ,OQ,PQ)

Branchburg, NJ · On-site

Applies scientific and technical knowledge to projects and responsible for timely project execution. * Lead process engineering activities in support of the product line, including: Process ...

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All JobsKnowledge Engineering JobsKnowledge Engineering Jobs in New York

Knowledge Engineering information

What is knowledge engineering?

Knowledge engineering is a field within artificial intelligence that focuses on creating systems capable of simulating human decision-making and reasoning. It involves gathering, organizing, and structuring information so that computers can use it to solve complex problems. Knowledge engineers work to build knowledge bases and rule-based systems, often collaborating with domain experts to codify expertise into a form that machines can process. This discipline is fundamental in the development of expert systems, intelligent agents, and modern AI applications.

What are the key skills and qualifications needed to thrive as a knowledge engineer?

To thrive as a Knowledge Engineer, you need a strong background in computer science, logic, and data modeling, often supported by a relevant degree. Familiarity with knowledge representation systems, ontologies, semantic web technologies, and tools like Protégé is typically required, along with experience in programming languages such as Python or Java. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with subject matter experts and translate complex information into structured formats. These skills are critical for building effective knowledge-based systems that drive intelligent decision-making and organizational efficiency.

How does a knowledge engineer typically collaborate with subject matter experts during a project?

Knowledge Engineers frequently work closely with subject matter experts (SMEs) to extract, structure, and formalize domain knowledge into usable formats for AI systems or knowledge bases. This collaboration often involves conducting interviews, facilitating workshops, and reviewing documentation to ensure complex concepts are accurately captured. Effective communication and iterative feedback are key, as Knowledge Engineers must bridge the gap between technical requirements and expert insights. This teamwork helps ensure that the resulting system is both technically sound and aligned with real-world practices.

What is the difference between Knowledge Engineering vs Data Scientist?

AspectKnowledge EngineeringData Scientist
Required CredentialsTypically degrees in computer science, AI, or related fields; certifications in knowledge systemsDegrees in statistics, computer science, or mathematics; certifications in data analysis or machine learning
Work EnvironmentDeveloping knowledge bases, expert systems, and AI applications in tech or research settingsAnalyzing data, building predictive models, and deriving insights in various industries
Employer & Industry UsageUsed in AI development, research institutions, and tech companiesUsed across finance, healthcare, marketing, and tech sectors

While both roles involve working with data and AI, Knowledge Engineers focus on creating structured knowledge bases and expert systems, whereas Data Scientists analyze data to extract insights and build predictive models. Understanding these differences helps in choosing the right career path or job focus.

How much does a knowledge engineer make?

The average salary for a knowledge engineer typically ranges from $80,000 to $130,000 annually, depending on experience, education, and location. Knowledge engineers often work with AI, machine learning, and data management tools, and advanced skills can lead to higher compensation.

How to become a knowledge engineer?

To become a knowledge engineer, typically a bachelor's degree in computer science, information systems, or a related field is required, along with skills in knowledge representation, logic, and programming languages such as Python or Java. Experience with artificial intelligence, machine learning, and knowledge management tools is also valuable, and some roles may prefer candidates with advanced degrees or certifications in relevant areas.

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze information, create ontologies, and use tools like knowledge bases and reasoning algorithms to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming are essential for this role.

What are popular job titles related to Knowledge Engineering jobs in New York?

For Knowledge Engineering jobs in New York, the most frequently searched job titles are:

What job categories do people searching Knowledge Engineering jobs in New York look for?

The top searched job categories for Knowledge Engineering jobs in New York are:

What cities in New York are hiring for Knowledge Engineering jobs?

Cities in New York with the most Knowledge Engineering job openings:

Knowledge Engineering jobs near you
Infographic showing various Knowledge Engineering job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution.

Knowledge Graph Engineer

Squirro

New York, NY • Remote

Full-time

Re-posted 10 days ago

Job description

We are looking for a Knowledge Graph Engineer to join our team in the US, supporting the Delivery team in designing, implementing, and deploying knowledge graph–driven SaaS solutions for enterprise customers.


What You’ll Do

As a Knowledge Graph Engineer, you will work closely with customers and internal product and engineering teams to design and deploy semantic and knowledge graph solutions that deliver measurable business value.


  • Client Engagement & Solution Delivery: Manage client engagements from pre-sales through onboarding, deployment, and training, ensuring successful adoption of knowledge graph–based solutions.
  • Semantic Modeling & Knowledge Graph Design: Develop and maintain taxonomies, ontologies, and classification models. Design semantic structures that align user needs with business objectives.
  • Cross-functional Collaboration: Collaborate with product, engineering, and delivery teams to translate customer requirements into scalable semantic and technical solutions.
  • Product Contribution & Customer Feedback: Gather and prioritize client requirements, contribute ideas to the product roadmap, and support product positioning through demos, content, and customer-facing activities.


What You Bring

You will support the Product and Delivery functions in building and deploying high-quality semantic solutions.


  • Strong Python experience
  • Experience in customer-facing roles within software or SaaS environments
  • Strong communication and presentation skills
  • Practical experience developing taxonomies, ontologies, and knowledge graphs
  • Experience managing human and/or machine classification
  • In-depth knowledge of semantic web standards (RDF, SKOS, OWL, SPARQL)
  • Familiarity with graph databases, particularly RDF graph databases
  • Familiarity with Large Language Models (LLMs) and Retrieval Augmented Generation (RAG)
  • Ability to collaborate effectively across technical and non-technical teams


What we offer


  • Drive growth in a dynamic, high-potential tech environment
  • Enjoy autonomy with our "freedom and responsibility" work approach
  • Collaborate with exceptional talent solving extraordinary challenges
  • Drive customer success and retention while enjoying a flexible environment focused on growth
  • Make a strategic impact while having fun with awesome colleagues


About Squirro

Squirro is the enterprise AI platform built for regulated industries, streamlining enterprise search and automating complex, custom workflows. Secure, private, scalable, permissions-aware, and fully auditable, the platform ensures that every result is accurate and verifiable. Squirro powers agentic AI applications that are grounded in the organization’s unique enterprise ontology.

Further information about AI-driven business insights can be found at:
https://squirro.com/