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Knowledge Engineering Jobs in Texas (NOW HIRING)

You'll partner closely with product, engineering, and design teams to drive the development of intelligent features grounded in real legal workflows, and your work will directly influence the ...

Minimum Requirements: * 3+ years of experience in ontology engineering, knowledge graph development, or semantic data modeling. * Strong proficiency in OWL, RDF, RDFS, SPARQL, and related W3C ...

Minimum Requirements: * 3+ years of experience in ontology engineering, knowledge graph development, or semantic data modeling. * Strong proficiency in OWL, RDF, RDFS, SPARQL, and related W3C ...

Principal Software Engineer (Python)

Austin, TX · On-site +1

$133K - $179K/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.

Principal Software Engineer (Python)

Dallas, TX · On-site +1

$133K - $179K/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.

Python knowledge * Engineering business process knowledge * Ability to diagnose and resolve complex technical problems. * Strong hands on knowledge of different JIRA configurations * Skill in ...

The candidate will work collaboratively within a Wood client company and apply extensive and comprehensive knowledge of I&C engineering principles and practices to the organization's products and ...

Senior Technical Engineer

Austin, TX · On-site

$103K - $142K/yr

Significant engineering, project management, and / or operational experience. * Has demonstrated competency within a discipline. Preferred Qualifications * Possesses a strong technical knowledge and ...

Senior Technical Engineer

Austin, TX · On-site

$103K - $142K/yr

Significant engineering, project management, and / or operational experience. * Has demonstrated competency within a discipline. Preferred Qualifications * Possesses a strong technical knowledge and ...

We bring together industry knowledge, engineering capabilities, and delivery experience across core systems, digital, data, analytics, cloud, and AI. Deloitte's Financial Services Industry practice ...

We bring together industry knowledge, engineering capabilities, and delivery experience across core systems, digital, data, analytics, cloud, and AI. Deloitte's Financial Services Industry practice ...

We bring together industry knowledge, engineering capabilities, and delivery experience across core systems, digital, data, analytics, cloud, and AI. Deloitte's Financial Services Industry practice ...

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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 domain data, create ontologies, and implement knowledge bases using tools like logic programming and semantic technologies. Strong analytical skills and understanding of data modeling 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 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.

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 also require proficiency with tools like ontologies, semantic web technologies, and knowledge representation languages.

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.
What are popular job titles related to Knowledge Engineering jobs in Texas? For Knowledge Engineering jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Knowledge Engineering jobs? Cities in Texas with the most Knowledge Engineering job openings:
Infographic showing various Knowledge Engineering job openings in Texas as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Associate, Legal Knowledge Engineering

Litera

Austin, TX • Hybrid

$115K - $133K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 5 days ago


Job description

Job Description

Ready to Help Shape the Future of Legal Tech?!

At Litera, we don't just build software, we transform how the world's top law firms operate. Every day, we RaiseTheBar for what's possible through AI, innovation, and solutions that power millions of legal professionals worldwide. If you're energized by scale, real impact, and meaningful challenges, you'll feel right at home here.

Where You'll Work

Hybrid: This is a hybrid role based in Toronto, Austin, Chicago, Denver, New Jersey, Philadelphia, or Raleigh with the expectations to be in office at least 3 days a week for collaboration and connection.

Why this Role Matters

As our Associate, Legal Engineering, you'll play a key role in shaping how Litera's AI-powered products understand and analyze complex legal documents. You'll partner closely with product, engineering, and design teams to drive the development of intelligent features grounded in real legal workflows, and your work will directly influence the accuracy, usability, and value our tools deliver to the world's leading law firms, professional service firms, and corporations. This is a high-visibility role ideal for someone who thrives in a fast-moving, collaborative environment and wants to make a measurable difference from day one.

What You'll Deliver

  • Product vision for legal AI. Partner with product, engineering, and design teams to define the roadmap for Kira and other Litera legal tech products, ensuring every feature reflects how lawyers actually work.

  • High-performing machine learning models. Develop and refine "smart fields" - ML algorithms that automatically locate key provisions in securities, financing, and other transactional documents - so clients spend less time on manual review.

  • Optimized generative AI experiences. Experiment with and validate LLM-driven prompting within Litera products, raising accuracy and usability for end users.

  • Domain expertise that keeps Litera ahead. Maintain deep awareness of developments in transactional law and continuously identify new document types and data points worth building into the platform.

  • Legally sound product workflows. Advise engineering teams on how legal processes work in practice, preventing design choices that would create friction for attorneys.

  • Scalable quality standards. Train and validate models across diverse document sets, ensuring consistent, reliable output that clients can trust at scale.

  • Process improvements and best practices. Identify inefficiencies in current workflows and recommend changes that accelerate delivery and improve product quality.

  • Client-ready solutions. Translate complex legal concepts into actionable product requirements that deliver measurable value to the world's leading firms and corporations.

We're committed to creating an inclusive environment. If you need accommodations at any point in the process or in the role, we're here to support you.

What You'll Bring

Must-Haves:

  • JD with active bar admission in at least one U.S. state or Canadian province.

  • Two or more years of transactional law experience at a law firm, in-house legal team, or legal service provider.

  • Strong interest in legal technology and artificial intelligence, with a willingness to experiment with new tools.

  • Exceptional attention to detail, analytical skills, and ability to manage multiple priorities simultaneously.

  • Excellent written and verbal communication skills paired with a client-service mindset.

  • Self-motivated and able to work independently while collaborating effectively across cross-functional teams.

Nice to Haves:

  • Experience in debt financing transactions.

  • Background in legal operations, legal program management, or contract management systems.

  • Hands-on exposure to AI, machine learning, or generative AI tools.

  • Prior experience working with or within a legal technology company.

We know great candidates don't always check every box. If you're excited about this role, we encourage you to apply.

What You'll Experience

  • A team that shows up. Work alongside people who collaborate, support one another, and lead with integrity.

  • Global Reach. Partner with teams around the world to solve complex challenges that matter.

  • Real opportunity for growth. Expand your impact through meaningful stretch opportunities, visibility and career development.

  • AI-driven innovation. Work at the intersection of legal technology, customer outcomes, and cutting-edge AI.

Pay Transparency for Colorado, Illinois, and New Jersey:

The base salary range for this role is $80,000 to $97,000 USD. Final compensation will be determined based on experience, skills, education, and other relevant qualifications. This role is also eligible to earn commission based on performance.

Pay Transparency for Ontario Applicants

The base salary range for this role is $115,000 to $133,000 CAD. Final compensation will be determined based on experience, skills, education, and other relevant qualifications. This role is also eligible to earn commission based on performance. In addition to base salary, Litera offers a comprehensive benefits package, including medical, dental, and vision coverage, retirement savings plan with company match, and incentive and recognition programs. Benefits are subject to eligibility requirements.

Litera is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.