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Knowledge Engineering Jobs in California (NOW HIRING)

Infosys Limited Digital

About the Role As a Principal - Knowledge Engineering and Decision Systems, you will operate at the intersection of formal knowledge representation, rules engine design, and AI-assisted compliance ...

Everlaw

GTM Knowledge Engineer

Oakland, CA · On-site +1

As our first GTM Knowledge Engineer, you'll sit at the intersection of Revenue Enablement, Revenue ... Custom GTM Agent Engineering: Design, code, and ship localized context-aware GTM Agents that solve ...

Everlaw

GTM Knowledge Engineer

Oakland, CA · On-site

As our first GTM Knowledge Engineer, you'll sit at the intersection of Revenue Enablement, Revenue ... Custom GTM Agent Engineering: Design, code, and ship localized context-aware GTM Agents that solve ...

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site +1

$144K - $194K/yr

Collaborate with the Knowledge Engineering team to build automated workflows for Ontology Management and Entity Linking , eliminating single-resource bottlenecks and manual curation constraints.

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site

$144K - $194K/yr

Collaborate with the Knowledge Engineering team to build automated workflows for Ontology Management and Entity Linking , eliminating single-resource bottlenecks and manual curation constraints.

Apple

Senior Data Engineer

San Francisco, CA · On-site

$124K - $169K/yr

Java or Scala 5+ years experience with big data platforms Familiarity with ML/AI workflows and feature engineering to support analytics, reporting, and machine learning use cases Knowledge ...

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Knowledge Engineering information

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 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 engineers make $500,000 a year?

Highly experienced engineers in specialized fields such as software engineering, data engineering, or systems architecture can earn $500,000 or more annually, especially in senior or executive roles at large technology companies. These positions often require advanced skills, certifications, and extensive industry experience, and may include bonuses and stock options that contribute to total compensation.

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 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 engineers make 200,000 a year?

Senior knowledge engineers, especially those with expertise in artificial intelligence, machine learning, and data science, can earn $200,000 or more annually. High salaries are often associated with extensive experience, advanced certifications, and working in industries like technology, finance, or consulting, typically in roles involving complex problem-solving and specialized tools.

How much does a knowledge engineer make?

A knowledge engineer's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI, machine learning, or data management can earn higher salaries. Many positions require proficiency with knowledge representation, ontologies, and tools like Protégé or OWL.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

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.
What are popular job titles related to Knowledge Engineering jobs in California? For Knowledge Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Knowledge Engineering jobs in California look for? The top searched job categories for Knowledge Engineering jobs in California are:
What cities in California are hiring for Knowledge Engineering jobs? Cities in California with the most Knowledge Engineering job openings:
Knowledge Engineering jobs near you

Principal, Business Consulting - Knowledge Engineering and Decision Systems

Infosys Limited Digital

On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 hours ago

Job description

Job details
Job Role
Principal - Business Consulting
Work Location
Atlanta, GA, Basking Ridge, NJ, Boston, MA, Chicago, IL, Dallas, TX, New York, NY, San Francisco, CA, Seattle, WA
State / Region / Province
California, Georgia, Illinois, Massachusetts, New Jersey, New York, Texas, Washington
Country
USA
Skills
Process|Consulting processes|Technology Consulting process
Domain
Consulting
Interest Group
Infosys Limited
Company
ITL USA
Requisition ID
148037BR
Salary min
154375
Salary max
193125
Do you find yourself drawn to problems where the rules are genuinely complex - where getting them wrong has real consequences and getting them right requires both rigor and deep systems thinking? Do you translate ambiguous, multi-layered complexity into formal structures that teams can build from?
If so, we want to speak with you. Infosys Consulting, the management and technology consulting unit of Infosys Ltd, is seeking a talented consultant to design and build a next-generation rules engine and knowledge graph in one of the most complex regulatory environments in financial services. Senior consultants seeking a demanding, high-visibility engagement with long-term growth potential will find both as part of our team.
About the Role
As a Principal - Knowledge Engineering and Decision Systems, you will operate at the intersection of formal knowledge representation, rules engine design, and AI-assisted compliance intelligence - translating complex, multi-jurisdictional regulatory requirements into a system that is computable, auditable, and maintainable at production scale.
Responsibilities
  • Serve as the primary consultant on the rules engine and knowledge graph workstream - owning the design approach and ensuring what gets built is correct, auditable, and maintainable
  • Design the ontology underpinning the knowledge graph - defining entities, properties, and relationships with particular attention to hierarchical inheritance, conflict resolution, and temporal validity across a complex multi-jurisdictional regulatory environment
  • Design the rules engine approach - how rules are represented as data rather than code, how they are evaluated against facts, how conflicts between jurisdictional levels are resolved explicitly and auditably
  • Produce consulting deliverables - design documents, ontology specifications, technical specifications - that are precise, complete, and unambiguous enough for engineering teams to build from
  • Work alongside our engineering team to ensure implementation reflects the design - identifying divergence early and resolving questions that surface during build
  • Lead discovery with client stakeholders - understanding current systems, data structures, workflow requirements, and constraints through structured workshops and working sessions
  • Communicate complex concepts clearly to both technical and non-technical client stakeholders
  • Support knowledge transfer - ensuring client teams understand what has been built well enough to maintain and extend it
  • Define how AI agent layers interact with the knowledge graph - how AI-assisted rule extraction, impact assessment, and decision support capabilities interface with the core rules system
  • Advise on correctness and auditability requirements for a system where AI enters structured knowledge pipelines
Basic Qualifications
  • Undergraduate degree in Computer Science, Engineering, Mathematics, or related discipline - or equivalent demonstrated experience
  • Excellent communication and presentation skills, both written and verbal - including the ability to present complex concepts to mixed technical and business audiences
  • Demonstrated experience designing production rules engines and/or designing or working with knowledge graphs for complex domains - including ontology design, temporal validity modeling, and hierarchical relationship modeling
  • Familiarity with graph database technologies - Neo4j, Amazon Neptune, or similar - at the design and modeling level
  • Familiarity with formal knowledge representation approaches - OWL, RDF, DMN, SPARQL, or similar - and understanding of when and why to apply them
  • Experience working in consulting or professional services contexts - facilitating workshops, engaging client stakeholders, managing technical communication across organizations
  • Highly motivated with strong analytical acumen and problem solving skills
  • Ability to travel as needed (typically up to 4 days/week) to client locations.
  • Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
Preferred Qualifications
Background in regulated industries where rules are complex, multi-jurisdictional, and correctness is non-negotiable - insurance, tax, healthcare, or financial services
The estimated total annual compensation (Base + Bonus) range for candidates based out on NJ, IL, NY, CA & WA will be $ 154,375 - $ 193,125
Benefits
Along with competitive pay, as a full-time Infosys employee you are also eligible for the following benefits:
  • Medical/Dental/Vision/Life Insurance
  • Long-term/Short-term Disability
  • Health and Dependent Care Reimbursement Accounts
  • Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
  • 401(k) plan and contributions dependent on salary level
  • Paid holidays plus Paid Time Off
About Us
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
EEO
Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.

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