Senior Semantic Platform Engineer

SARACA; Dallas (TX); In loco; USD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

SARACA in Dallas seeks a hands-on Semantic Platform Engineer to design and deploy an ontology-driven knowledge platform. You will build RDF graphs, SPARQL queries, SHACL checks, and Azure deployments to support AI-powered diagnostics.

You will collaborate with data engineers and software teams to release portable, containerized solutions, implement CI/CD, and ensure data quality across multi-cloud environments.

Competenze

• 4+ years building production-grade semantic data platforms.
• Proficiency with RDF/RDFS, OWL 2, SPARQL 1.1, SHACL.
• Strong Python skills with RDFLib or equivalent.
• Experience with Git, automated testing, and CI/CD.

Mansioni

• Deploy and configure ontology engine and semantic repository.
• Develop data pipelines to Azure for semantic data.
• Build portable deployments with IaC for multi-cloud.
• Expose knowledge graphs via read-only endpoints for AI agents.
• Manage ontologies and semantic models with CI/CD.
• Implement SPARQL tests and SHACL validation.
• Create documentation and sample queries for AI grounding.
• Maintain competency questions and historical data tests.
• Collaborate with domain experts and engineers.

Conoscenze

Ontology engineering

RDF/OWL

SPARQL

SHACL

Python

RDFLib

Git & CI/CD

Azure

Databricks

Containerization

Knowledge graphs

Strumenti

GraphDB

Stardog

RDFox

Apache Jena/Fuseki

Protégé

Descrizione del lavoro

Company Description SARACA is a global engineering R&D services company serving 25+ Fortune 500 customers across MedTech, Aerospace, Rail, Automotive, Semiconductor, Defense, and Farm industries. The organization is ISO 13485 certified and has extensive experience with next-generation medical devices, including embedded software, UI/UX, mechanical, systems, and product testing. SARACA offers specialized expertise in IEC 62304, EU MDR, and a wide range of scientific and regulatory documentation for MedTech. A leadership team with deep product engineering experience and 400+ engineers and management consultants supports complex onsite and offsite projects worldwide. As an equal-opportunity employer, SARACA promotes a culture of innovation and learning, focused on helping customers grow faster and lead their industries.

ob Title: Semantic Platform Engineer

Start Date: Immediate Availability

Job Description

Our client is developing an AI-driven Energy Intelligence service that transforms condition-based maintenance (CBM) analytics into normalized equipment health scores, contextual diagnostics, and prioritized action plans for critical data-center power equipment, including UPS systems and busways.

The Semantic Platform Engineer will design, deploy, and maintain a semantic data platform that provides knowledge graphs and asset relationships to diagnostic AI agents. The role involves ontology engineering, RDF triple-store deployment, data pipeline development, Azure infrastructure, and automated testing of semantic models.

Key Responsibilities

• Deploy and configure the existing ontology engine and establish a shared semantic repository for partner teams.
• Develop data pipelines to load resolved data into the semantic repository on Azure, alongside existing CBM analytics in Databricks.
• Build portable, containerized deployments using Infrastructure as Code (IaC) to support future multi-cloud migration.
• Expose knowledge graphs through documented, read-only query endpoints for diagnostic AI agents and monitor query performance.
• Manage ontologies, mappings, and semantic models as version-controlled code with automated testing and CI/CD integration.
• Implement SPARQL-based competency tests and SHACL validation to ensure semantic consistency and data quality.
• Create technical documentation, schema summaries, and example queries to support AI agent grounding.
• Maintain competency questions and expected answers to validate diagnostic agents against historical maintenance incidents.
• Collaborate with domain experts, data engineers, and software developers to translate business requirements into effective semantic models.

Mandatory Skills & Qualifications

• 4+ years of experience building and deploying production-grade knowledge graphs, ontologies, or semantic data platforms.
• Strong hands-on expertise in RDF/RDFS, OWL 2, SPARQL 1.1, and SHACL.
• Proficiency in Python, including libraries such as RDFLib, pySHACL, or equivalent tools.
• Experience with Git, automated testing, and CI/CD pipelines.
• Hands-on experience deploying and operating RDF triple stores or reasoning engines such as GraphDB, Stardog, RDFox, or Apache Jena/Fuseki.
• Experience with Microsoft Azure, containers, Infrastructure as Code, and CI/CD deployment practices.
• Experience working with Databricks and integrating semantic data platforms with data-processing environments.
• Strong communication skills, with the ability to collaborate with domain experts and explain ontology modelling decisions to software engineering teams.

Preferred Qualifications

• Knowledge of electrical power systems or data-center infrastructure, including UPS, busways, switchgear, and PDUs.
• Familiarity with maintenance concepts such as failure modes, FMEA, and condition monitoring.
• Experience with standard vocabularies and ontologies such as Brick, RealEstateCore, ASHRAE 223, SOSA/SSN, QUDT, ISO 14224, or IEC 81346.
• Experience integrating knowledge graphs with LLMs using GraphRAG, text-to-SPARQL, or ontology-grounded prompting.
• Familiarity with property graph technologies such as Neo4j and Cypher, including an understanding of RDF versus property graph approaches.
• Experience with ontology modelling and schema tools such as Protégé, TopBraid, or LinkML.

Ideal Candidate Profile

A hands-on Semantic Platform Engineer with strong production experience in ontology engineering, RDF knowledge graphs, SPARQL, SHACL, Python, and Azure-based deployments. The candidate should be capable of building a reliable, testable, and portable semantic platform that provides accurate asset context and relationship data to AI-powered diagnostic systems.