Ontology Engineering

Ontology Engineering Jobs

3 jobs found

15d ago

Palantir Data Engineer

Guidehouse McLean, VA

McLean, VA

15d ago

$113k - $188k/yr Full time Analytics Big Data Bigdata

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Job Description

This onsite role in McLean, VA offers a competitive compensation range of USD 113,000 to 188,000 per year, along with a comprehensive benefits package and strong pathways for professional growth. You will join Guidehouse as a Palantir Data Engineer focused on designing and operating ontology driven data products in Palantir Foundry. The work centers on semantic data modeling, governance, and analytics to support case management and operational workflows. The environment emphasizes collaboration across platform engineering, security, analytics, and application teams, with a clear commitment to data quality and governance.

Responsibilities

Create, implement, and maintain Palantir Foundry Ontologies, defining entities, relationships, properties, actions, and permissions.
Translate business processes and domain requirements into clear, reusable entity and relationship models.
Maintain semantic consistency across datasets through standardized definitions, naming conventions, and relationship patterns.
Evolve ontologies over time while preserving lineage, backward compatibility, and data contracts.
Design ingestion pipelines into Foundry from APIs, relational databases, object storage, file drops, and external partners.
Develop transformation logic that materializes ontological entities and relationships from raw and curated data.
Implement incremental processing and change data capture to keep ontology backed data current.
Optimize pipeline performance and reliability while distinguishing raw, curated, and ontology backed layers.
Produce analysis ready datasets that power case views, entity timelines, dashboards, cohort analyses, and trend reporting.
Enable self service analytics by delivering intuitive, well documented ontology backed datasets.
Support both human workflows and analytical or machine learning consumption from the same semantic foundation.
Document datasets and entities with ownership, descriptions, and business definitions.
Maintain end to end lineage from source systems through transformations into ontological entities.
Enforce policy based access controls and secure handling aligned to compliance requirements.
Operationalize data quality checks for freshness, completeness, and validity tied to mission critical entities.
Monitor pipelines and ontology backed datasets using metrics, logs, and alerts.
Troubleshoot failures, perform root cause analysis, and implement preventive improvements.
Support environment promotion practices (DEV, TEST, PRE-PROD, PROD) with repeatable and auditable processes.
Collaborate with platform engineering, security, analytics, and application teams to align ontology design with operational needs.
Communicate complex ontology and data concepts clearly to technical and non technical stakeholders.
Participate in design and architecture reviews related to ontology evolution and data modeling standards.

Requirements

Bachelor's degree required.
Minimum of 3 years of experience building and operating production data pipelines and data models.
Hands on experience with Palantir Foundry or strong data engineering experience with the ability to ramp quickly.
Palantir Foundry Ontology experience, including entity and relationship modeling.
Palantir Foundry Ontology experience, including ontology backed actions and workflows.
Palantir Foundry Ontology experience, including permissioning and governance within the ontology.
Strong SQL proficiency and experience with at least one data engineering language (Python preferred; Scala/Java acceptable).
Experience implementing ETL or ELT pipelines, incremental processing, and transformation best practices.
Familiarity with governance fundamentals, including metadata, lineage, access controls, and data quality.
Strong communication skills and experience collaborating directly with product and mission stakeholders.

Technologies

Palantir Foundry
Palantir Foundry Ontology
SQL
Python
Scala
Java
Palantir AIP
Databricks
Spark
Lakehouse architectures

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Discretionary variable incentive bonus eligibility
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life Insurance
Health Savings Account, Dental/Vision and Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend

Nice to Have

Palantir Application Developer experience building operational applications and workflows on the ontology
Bachelor’s degree in Engineering, Computer Science, Information Systems, or related field, or equivalent practical experience
Palantir AIP experience including ontology-backed document understanding and summarization
Palantir AIP experience covering entity extraction and enrichment
Palantir AIP experience with human-in-the-loop review and governance controls
Experience using AI copilots for pipeline development, transformations, ontology evolution, and code review
Applying generative AI to improve developer productivity while upholding data quality and governance
Experience supporting ontology-first designs for case management systems
Knowledge of entity resolution, relationship extraction, and graph-based modeling
Familiarity with Databricks, Spark, or lakehouse architectures in hybrid environments
Exposure to CI/CD practices for data pipelines and ontology changes

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17d ago

Palantir Data Engineer

Guidehouse Inc. Washington, DC

Washington, DC

17d ago

$113k - $188k/yr Full time Data Architecture Data Engineer Data Governance

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Job Description

Guidehouse Inc. seeks a Palantir Data Engineer in Washington, DC onsite to design, build, and operate ontology-driven data products in Palantir Foundry, focusing on semantic modeling, governance, and ontology-backed analytics for case management and operations.

Responsibilities

Design, implement, and maintain Palantir Foundry ontologies, covering entities, relationships, properties, actions, and permissions.
Convert business processes and domain requirements into clear, reusable entity-relationship models.
Maintain semantic consistency across datasets by enforcing standardized definitions, naming conventions, and relationship patterns.
Evolve ontologies over time while preserving lineage, backward compatibility, and data contracts.
Build ingestion pipelines into Foundry from APIs, relational databases, object storage, file drops, and external partners.
Develop transformation logic to materialize ontological entities and relationships from raw and curated data.
Implement incremental processing and change data capture to keep ontology-backed data current.
Optimize pipeline performance and reliability while preserving clear separation between raw, curated, and ontology-backed layers.
Produce analysis-ready datasets powering case views, entity timelines, dashboards, cohort analyses, and trend reporting.
Enable self-service analytics by ensuring ontology-backed datasets are intuitive, well-documented, and reusable.
Support both human workflows (case review, operations) and analytical/ML consumption from the same semantic foundation.
Document datasets and entities with owners, descriptions, and business definitions.
Maintain end-to-end data lineage from source systems through transformations into ontological entities.
Implement policy-based access controls and secure handling aligned to compliance requirements.
Operationalize data quality checks for freshness, completeness, and validity tied to mission-critical entities.
Monitor pipelines and ontology-backed datasets using metrics, logs, and alerts.
Troubleshoot failures, perform root-cause analysis, and apply preventive improvements.
Support environment promotion practices (DEV, TEST, PRE-PROD, PROD) with repeatable and auditable processes.
Collaborate with platform engineering, security, analytics, and application teams to align ontology design with operational needs.
Communicate complex ontology and data concepts clearly to both technical and non-technical stakeholders.
Participate in design and architecture reviews related to ontology evolution and data modeling standards.

Requirements

Bachelor’s degree is required.
Minimum of 3 years building and operating production data pipelines and data models.
Hands-on experience with Palantir Foundry, or strong data engineering background with the ability to ramp quickly.
Palantir Foundry Ontology experience including entity and relationship modeling.
Palantir Foundry Ontology experience including ontology-backed actions and workflows.
Palantir Foundry Ontology experience including permissioning and governance within the ontology.
Strong SQL proficiency and experience with at least one data engineering language (Python preferred; Scala/Java acceptable).
Experience implementing ETL/ELT pipelines, incremental processing, and transformation best practices.
Familiarity with governance fundamentals including metadata, lineage, access controls, and data quality.
Strong communication skills and experience working directly with product and mission stakeholders.

Technologies

Palantir Foundry
Palantir Foundry Ontology
SQL
Python
Scala
Java
Databricks
Spark

Salary

$113,000 - $188,000 per year

Benefits

Medical, prescription drug, dental, and vision insurance
Personal and family sick time plus company-paid holidays
Discretionary variable incentive bonus eligibility
Parental leave and adoption assistance
401(k) retirement plan
Basic and supplemental life insurance
Health Savings Account, dental/vision, and dependent care flexible spending accounts
Short-term and long-term disability insurance
Student loan payoff assistance
Tuition reimbursement and opportunities for personal development
Skills development and certifications
Employee referral program
Corporate-sponsored events and community outreach
Emergency back-up childcare program
Mobility stipend

Travel Required

Up to 25%

Clearance Required

Ability to Obtain Public Trust

What you will need

Bachelor’s degree is required.
Minimum of 3 years building and operating production data pipelines and data models.
Hands-on Palantir Foundry experience, or strong data engineering background with the ability to ramp quickly.
Palantir Foundry Ontology experience including entity and relationship modeling.
Palantir Foundry Ontology experience including ontology-backed actions and workflows.
Palantir Foundry Ontology experience including permissioning and governance within the ontology.
Strong SQL proficiency and experience with at least one data engineering language (Python preferred; Scala/Java acceptable).
Experience implementing ETL/ELT pipelines, incremental processing, and transformation best practices.
Familiarity with governance fundamentals including metadata, lineage, access controls, and data quality.
Strong communication skills and experience working directly with product and mission stakeholders.

What would be nice to have

Palantir Application Developer experience building operational applications and workflows on top of the ontology.
Bachelor’s degree in Engineering, Computer Science, Information Systems, or related field or equivalent practical experience.
Palantir AIP experience including ontology-backed document understanding and summarization; entity extraction and enrichment; human-in-the-loop review with governance controls.
Generative AI assisted coding experience, such as AI copilots for pipelines, transformations, ontology evolution, and code review; applying generative AI to boost developer productivity while maintaining data quality and governance.
Experience supporting ontology-first designs for case management systems.
Knowledge of entity resolution, relationship extraction, and graph-based modeling.
Familiarity with Databricks, Spark, or lakehouse architectures in hybrid environments.
Exposure to CI/CD practices for data pipelines and ontology changes.

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25d ago

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

Salesforce San Francisco, CA

San Francisco, CA

25d ago

$149k - $286k/yr Full time AI Data Engineer Data Engineering

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Job Description

Overview

Salesforce stands as a leader in AI powered customer relationship management, driven by teams of agents delivering customer success. We seek ambitious professionals who want to advance business and society through AI while upholding Salesforce’s core values. If you are excited about the future of AI in enterprise settings, this opportunity is for you.

The Opportunity

Salesforce is building the next generation Enterprise Knowledge Graph platform to empower AI driven experiences, agent centered applications, semantic search, enterprise data discovery, and intelligent decision making across the organization. We are hiring for both a Senior Member of Technical Staff (SMTS) and a Lead Member of Technical Staff (LMTS) to join the Enterprise Knowledge Graph and AI Engineering team.

Your Responsibilities

Design and Implement: Develop and scale the Enterprise Knowledge Graph platform components with a focus on performance, throughput, reliability, high availability, and data integrity. LMTS leads hands on design and subsystem implementation; SMTS contributes production grade code.
Graph and Ontology Engineering: Create graph data models, craft complex queries, and build scalable data pipelines to map structured and unstructured data to enterprise ontologies and taxonomies. LMTS also designs enterprise ontologies, taxonomies, semantic layers, entity resolution frameworks, graph APIs, and vector search capabilities to support advanced RAG and agentic workflows.
Semantic Routing: Develop Python based semantic routing frameworks to parse, classify, and dynamically direct incoming queries to the appropriate knowledge graph indexes or vector databases. LMTS designs, optimizes, and productionizes routing frameworks at scale, steering queries to relevant graphs, ontology subgraphs, or vector stores.
AI Tooling and Automation: Build and integrate AI powered developer tools and engineering automation platforms leveraging ecosystems such as Claude, Cursor, Windsurf, AI Agents, and Model Context Protocol (MCP) frameworks. LMTS also develops, deploys, and optimizes these tools and drives strategy and productionization.
Data Integration: Create scalable data pipelines and engineering patterns to ingest, transform, and orchestrate structured, unstructured, and third party data sources into graph based platforms mapped to enterprise ontologies.
Feature Ownership and Technical Execution: Own the technical delivery of specific platform features from concept through design, coding, testing, and production deployment. LMTS translates high level technical visions into concrete system blueprints, ontology schemas, and execution plans.
Code Quality and Rigor: Engage in code reviews, write comprehensive automated unit and integration tests, and uphold engineering standards and operational best practices.
Technical Mentorship: Provide technical guidance to the engineering team. SMTS mentors MTS and Associate engineers; LMTS offers day-to-day guidance, code reviews, and design direction to SMTS, MTS, and associated engineers to foster technical rigor and operational maturity.
Cross-Functional Collaboration: Work closely with Lead and Principal Engineers, Product Managers, and Data Engineering teams to deliver robust features aligned with enterprise AI priorities. LMTS also partners with PMTS engineers and Ontology governance boards to ensure alignment with AI infrastructure standards.
Evaluate and Innovate: Conduct deep dive evaluations of emerging graph technologies, ontology modeling tools, semantic reasoning frameworks, vector databases, and AI tooling to continuously modernize the platform.

You're Our Person If

SMTS

Experience: 8+ years of hands on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
Education: A related technical degree is required.
Core Programming: Expert level backend coding skills with strong fluency in Python and standard object oriented or functional programming languages.
Semantic Routing and AI: Hands on experience building and deploying custom semantic routers using Python, embeddings, LangChain, or cosine similarity, alongside Retrieval-Augmented Generation architectures, vector search platforms, and AI workflows.
Graph and Ontology Fundamentals: Solid experience with graph databases and semantic web concepts such as Neo4j, RDF/OWL, SPARQL, and property graphs, mapping data to structured taxonomies.
Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows such as Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks.
Distributed Systems and Cloud: Proven ability to build cloud native applications on AWS, GCP, or Azure using microservices, REST or gRPC APIs, and event driven data streaming (Kafka).
Delivery: A track record of owning and delivering complex features in an agile production environment.

LMTS

Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms.
Education: A related technical degree is required.
Ontology and Graph Expertise: Substantial hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems.
Tooling and Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools such as Neo4j, TopQuadrant, Protégé, RDF/OWL, SPARQL, SHACL, property graphs, and semantic reasoning frameworks.
AI and Retrieval: Proven experience implementing graph powered AI solutions, vector search platforms, Retrieval-Augmented Generation architectures, and orchestrating agentic workflows.
Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routing.

Location

San Francisco, California 94105

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Ontology Engineering Jobs

Palantir Data Engineer

Palantir Data Engineer

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

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