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Semantic Solutions Architect Jobs (NOW HIRING)

Simplex

Solutions Architect- Databricks

Hartford, CT · Remote

$170K - $200K/yr

As a Solutions Architect, you will lead customer workshops, work with enterprise data platforms, and learn semantic technologies. You will work closely with clients to understand their unique ...

Simplex

Solutions Architect- Databricks

Hartford, CT · Remote

$63.50 - $83.75/hr

As a Solutions Architect, you will lead customer workshops, work with enterprise data platforms, and learn semantic technologies. You will work closely with clients to understand their unique ...

Simplex

Solutions Architect- Databricks

Hartford, CT · On-site +1

$170K - $200K/yr

As a Solutions Architect, you will lead customer workshops, work with enterprise data platforms, and learn semantic technologies. You will work closely with clients to understand their unique ...

Simplex

Solutions Architect- Databricks

Hartford, CT · Remote

$63.50 - $83.75/hr

As a Solutions Architect, you will lead customer workshops, work with enterprise data platforms, and learn semantic technologies. You will work closely with clients to understand their unique ...

Ontio AI

AI Platform Solutions Architect

San Francisco, CA · On-site

$74.25 - $97.75/hr

Configure and optimize platform capabilities, including data integrations, semantic context ... Solutions Architecture, Enterprise Architecture, Technical Consulting, or similar customer-facing ...

Ontio AI

$46.50 - $61.25/hr

Configure and optimize platform capabilities, including data integrations, semantic context ... Solutions Architecture, Enterprise Architecture, Technical Consulting, or similar customer-facing ...

Spaulding Ridge

Data Solutions Architect

Chicago, IL · On-site

What You Will Do As a Data Solutions Architect , you'll be responsible for scoping, designing ... Ability to advise clients on when to use dashboards, semantic layers, data products, custom ...

SHI

Solutions Architect - Data Visualization

The Solutions Architect defines the analytics approach, designs reporting and semantic architectures, leads customer engagements, and provides oversight throughout delivery of the visualization ...

Vizient

Principal Solutions Architect

Chicago, IL

In this role, you will serve as a Principal Enterprise Solutions Architect, driving the ... Establish architectural patterns for data products, semantic layers, domain models, and cross ...

Vizient

Principal Solutions Architect

Irving, TX

In this role, you will serve as a Principal Enterprise Solutions Architect, driving the ... Establish architectural patterns for data products, semantic layers, domain models, and cross ...

Aaa-Washington

The BI Solutions Architect designs semantic models, administers enterprise BI platforms, and maintains governance standards that enable trusted, scalable analytics. By delivering high-quality ...

Fivetran, Inc.

Partner Solutions Architect

California, MO · On-site

$56.50 - $74.25/hr

About the role We're looking for a Partner Solutions Architect to join Fivetran + dbt Labs and own ... The ISVs in scope span business intelligence, semantic and metrics consumption, catalog and ...

Fivetran, Inc.

$46.50 - $61.25/hr

About the role We're looking for a Partner Solutions Architect to join Fivetran + dbt Labs and own ... The ISVs in scope span business intelligence, semantic and metrics consumption, catalog and ...

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Semantic Solutions Architect information

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$74.5K

$150.2K

$198K

How much do semantic solutions architect jobs pay per year?

As of Sep 11, 2026, the average yearly pay for semantic solutions architect in the United States is $150,181.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,500.00 and $172,000.00 per year, depending on experience, location, and employer.

What is a semantic solutions architect?

A Semantic Solutions Architect is a specialized IT professional who designs and implements systems that leverage semantic technologies, such as knowledge graphs, ontologies, and linked data, to improve data integration, search, and analysis. They work closely with business and technical stakeholders to create solutions that enable smarter data connectivity and context-aware applications. Their responsibilities often include evaluating semantic tools, defining architecture, and ensuring interoperability between diverse data sources. This role is critical in organizations that need to extract meaningful insights from complex and heterogeneous data.

How does a semantic solutions architect collaborate with cross-functional teams during project implementation?

As a Semantic Solutions Architect, you will frequently work alongside data engineers, software developers, and domain experts to design and integrate semantic technologies into existing systems. Collaboration often involves translating business requirements into technical solutions, establishing ontologies, and ensuring data consistency across platforms. Effective communication is essential, as you’ll bridge the gap between technical and non-technical stakeholders to deliver scalable and meaningful data architectures. Regular meetings and iterative feedback are common to align project goals and address challenges as they arise.

What are the key skills and qualifications needed to thrive as a semantic solutions architect, and why are they important?

To thrive as a Semantic Solutions Architect, you need expertise in ontology modeling, semantic technologies (like RDF and OWL), and a strong background in computer science or information systems. Familiarity with tools such as Protégé, SPARQL endpoints, and graph databases, as well as relevant certifications in semantic web or enterprise architecture, is highly valuable. Exceptional analytical abilities, problem-solving skills, and effective communication are crucial for translating business requirements into semantic solutions and collaborating with stakeholders. These skills ensure the successful design and implementation of scalable, interoperable data architectures that drive organizational insights and efficiency.

What is the difference between Semantic Solutions Architect vs Data Engineer?

AspectSemantic Solutions ArchitectData Engineer
Required credentialsBachelor's in CS, Data Science, or related; certifications in data modeling or cloud platformsBachelor's in CS, Software Engineering, or related; certifications in cloud or data tools
Work environmentDesigns data semantics, ontologies, and integration solutions in enterprise settingsBuilds and maintains data pipelines, databases, and ETL processes
Employer/industry usageUsed in data-driven organizations focusing on data semantics and knowledge graphsCommon in tech, finance, and healthcare sectors managing large-scale data systems

The Semantic Solutions Architect focuses on designing data semantics and integration strategies, while the Data Engineer builds and maintains data pipelines and infrastructure. Both roles require strong technical skills and often collaborate but serve different functions within data management.

What are popular job titles related to Semantic Solutions Architect jobs?

For Semantic Solutions Architect jobs, the most frequently searched job titles are:

Infographic showing various Semantic Solutions Architect job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 85% Full Time, 8% Part Time, and 6% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $150,181 per year, or $72.2 per hour.

Agentic AI / Semantic Solutions Architect

Atlanta, GA • On-site

Staffingine LLC
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Staffingine LLCexternal

Contractor

Re-posted 28 days ago

Job description

Job Title: Agentic AI / Semantic Solutions Architect
Job Location: Atlanta, Georgia, USA
Job Type: Contract

Job Description:

  • Architect and design agentic AI workflows that consume outputs from semantic layers, including knowledge graphs, ontologies, and metadata catalogs
  • Develop and prototype GraphRAG pipelines that combine graph traversal with vector-based retrieval for accurate, domain-grounded responses
  • Define and implement context engineering strategies, including metadata injection, chunking, and semantic optimization for LLM prompts
  • Design and build Model Context Protocol (MCP) server patterns to enable seamless interaction between agents and semantic data systems
  • Develop LLM orchestration workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or AutoGen
  • Build pipelines for automated metadata extraction and semantic tagging using NLP and LLM-based approaches
  • Collaborate with Semantic Data Architects to ensure ontologies and graph structures are optimized for agent traversal and querying
  • Prototype agent-based solutions for business use cases such as:
    • Credit risk analysis
    • Customer data onboarding workflows