Responsibilities
Peraton Labs is seeking a Senior Data Engineer to help design build and operationalize the data foundations supporting advanced AI-enabled capabilities. This role will focus on transforming complex structured and unstructured information into graph-aware semantically meaningful data products that can support analytics reasoning retrieval and agentic workflows.
We are looking for a candidate who combines strong data engineering execution with meaningful experience in knowledge graphs semantic representations NLP-derived structure and graph-based analysis. This may come from a traditional data engineering background with hands-on knowledge graph experience or from a research-oriented knowledge graph / semantic systems background paired with proven implementation ability.
The ideal candidate for this role should be comfortable working across data pipelines semantic modeling graph representations and AI-enabled data architectures. You should be comfortable moving between concept and implementation helping shape how knowledge is extracted structured linked and made usable for downstream AI systems.
Key responsibilities may include but are not limited to:
- Design build and maintain scalable data pipelines supporting graph-based and AI-enabled workflows
- Develop data models and processing approaches that transform raw structured and unstructured data into semantically meaningful graph-oriented representations
- Contribute to the creation enrichment and operationalization of knowledge graphs supporting retrieval reasoning entity relationships and advanced analytics
- Support ingestion normalization linking and transformation of data into graph-compatible formats such as RDF and related semantic representations
- Apply experience in areas such as NLP AMR UMR semantic parsing graph analysis or ontology-informed data modeling to improve how information is structured and connected
- Build data pipelines and engineering workflows that support graph-centric applications including AI-enabled search contextual retrieval and decision support
- Partner with AI/ML platform and software engineering teams to ensure graph and semantic data assets are usable within production-oriented systems
- Help define approaches for entity resolution relationship extraction semantic enrichment metadata management and graph quality validation
- Contribute to architectures that support agentic AI workflows by enabling richer data context structured memory and relationship-aware information access
- Work with a mix of structured semi-structured and unstructured data sources to improve interoperability and downstream usability
- Support graph analysis and exploration efforts that inform system design data relationships and capability development
- Ensure data engineering solutions are maintainable scalable and aligned to operational and mission needs
- Document data flows graph models transformation logic and engineering decisions clearly for technical stakeholders
Qualifications
Required Qualifications
- Minimum of BS with 12 years of experience MS with 10 YoE or PhD with 7 YoE in data engineering knowledge graph engineering semantic systems NLP-enabled data processing or related technical roles
- Strong hands-on experience building and maintaining data pipelines in modern engineering environments
- Demonstrated experience with knowledge graphs graph data models or semantic data architectures
- Experience within one or more of the following areas: RDF graph analysis semantic representation ontology-informed data modeling AMR UMR or NLP-driven structured extraction
- Strong hands-on experience with Python JavaScript/TypeScript and SQL for data transformation and pipeline development plus familiarity with graph and semantic tooling such as Neo4j/Neptune/GraphDB platforms
- Experience working with both structured and unstructured data in support of downstream analytics or AI/ML use cases
- Ability to translate complex source data into usable high-quality representations for graph-based or semantic systems
- Strong understanding of data quality schema design metadata transformation logic and scalable data workflows
- Ability to operate effectively in highly technical environments where requirements may evolve and where both rigor and adaptability matter
- Strong written and verbal communication skills with the ability to explain technical tradeoffs clearly across engineering and non-engineering stakeholders
- US Citizenship is a requirement for this position
Preferred Qualifications
- Experience with agentic AI systems or workflows that rely on structured context memory planning or relationship-aware retrieval
- Experience with GraphRAG or related graph-enhanced retrieval architectures
- Familiarity with graph databases triplestores semantic query languages or related tooling
- Experience supporting entity resolution relationship extraction semantic search or contextual retrieval workflows
- Background in NLP semantic parsing knowledge representation or computational linguistics
- Experience designing systems that connect knowledge representation approaches to operational AI applications
- Familiarity with ontology development schema alignment or semantic interoperability challenges
- Exposure to mission government defense or regulated technical environments
- Advanced degree in computer science data science computational linguistics AI/ML or a related field
Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the worlds leading mission capability integrator and transformative enterprise IT provider we deliver trusted highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land sea space air and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day our employees do the cant be done by solving the most daunting challenges facing our customers. Visit to learn how were keeping people around the world safe and secure.
Target Salary Range
$135000 - $216000. This represents the typical salary range for this position. Salary is determined by various factors including but not limited to the scope and responsibilities of the position the individuals experience education knowledge skills and competencies as well as geographic location and business and contract considerations. Depending on the position employees may be eligible for overtime shift differential and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer including disability and protected veterans or other characteristics protected by law.
Required Experience:
Senior IC
ResponsibilitiesPeraton Labs is seeking a Senior Data Engineer to help design build and operationalize the data foundations supporting advanced AI-enabled capabilities. This role will focus on transforming complex structured and unstructured information into graph-aware semantically meaningful data ...
Responsibilities
Peraton Labs is seeking a Senior Data Engineer to help design build and operationalize the data foundations supporting advanced AI-enabled capabilities. This role will focus on transforming complex structured and unstructured information into graph-aware semantically meaningful data products that can support analytics reasoning retrieval and agentic workflows.
We are looking for a candidate who combines strong data engineering execution with meaningful experience in knowledge graphs semantic representations NLP-derived structure and graph-based analysis. This may come from a traditional data engineering background with hands-on knowledge graph experience or from a research-oriented knowledge graph / semantic systems background paired with proven implementation ability.
The ideal candidate for this role should be comfortable working across data pipelines semantic modeling graph representations and AI-enabled data architectures. You should be comfortable moving between concept and implementation helping shape how knowledge is extracted structured linked and made usable for downstream AI systems.
Key responsibilities may include but are not limited to:
- Design build and maintain scalable data pipelines supporting graph-based and AI-enabled workflows
- Develop data models and processing approaches that transform raw structured and unstructured data into semantically meaningful graph-oriented representations
- Contribute to the creation enrichment and operationalization of knowledge graphs supporting retrieval reasoning entity relationships and advanced analytics
- Support ingestion normalization linking and transformation of data into graph-compatible formats such as RDF and related semantic representations
- Apply experience in areas such as NLP AMR UMR semantic parsing graph analysis or ontology-informed data modeling to improve how information is structured and connected
- Build data pipelines and engineering workflows that support graph-centric applications including AI-enabled search contextual retrieval and decision support
- Partner with AI/ML platform and software engineering teams to ensure graph and semantic data assets are usable within production-oriented systems
- Help define approaches for entity resolution relationship extraction semantic enrichment metadata management and graph quality validation
- Contribute to architectures that support agentic AI workflows by enabling richer data context structured memory and relationship-aware information access
- Work with a mix of structured semi-structured and unstructured data sources to improve interoperability and downstream usability
- Support graph analysis and exploration efforts that inform system design data relationships and capability development
- Ensure data engineering solutions are maintainable scalable and aligned to operational and mission needs
- Document data flows graph models transformation logic and engineering decisions clearly for technical stakeholders
Qualifications
Required Qualifications
- Minimum of BS with 12 years of experience MS with 10 YoE or PhD with 7 YoE in data engineering knowledge graph engineering semantic systems NLP-enabled data processing or related technical roles
- Strong hands-on experience building and maintaining data pipelines in modern engineering environments
- Demonstrated experience with knowledge graphs graph data models or semantic data architectures
- Experience within one or more of the following areas: RDF graph analysis semantic representation ontology-informed data modeling AMR UMR or NLP-driven structured extraction
- Strong hands-on experience with Python JavaScript/TypeScript and SQL for data transformation and pipeline development plus familiarity with graph and semantic tooling such as Neo4j/Neptune/GraphDB platforms
- Experience working with both structured and unstructured data in support of downstream analytics or AI/ML use cases
- Ability to translate complex source data into usable high-quality representations for graph-based or semantic systems
- Strong understanding of data quality schema design metadata transformation logic and scalable data workflows
- Ability to operate effectively in highly technical environments where requirements may evolve and where both rigor and adaptability matter
- Strong written and verbal communication skills with the ability to explain technical tradeoffs clearly across engineering and non-engineering stakeholders
- US Citizenship is a requirement for this position
Preferred Qualifications
- Experience with agentic AI systems or workflows that rely on structured context memory planning or relationship-aware retrieval
- Experience with GraphRAG or related graph-enhanced retrieval architectures
- Familiarity with graph databases triplestores semantic query languages or related tooling
- Experience supporting entity resolution relationship extraction semantic search or contextual retrieval workflows
- Background in NLP semantic parsing knowledge representation or computational linguistics
- Experience designing systems that connect knowledge representation approaches to operational AI applications
- Familiarity with ontology development schema alignment or semantic interoperability challenges
- Exposure to mission government defense or regulated technical environments
- Advanced degree in computer science data science computational linguistics AI/ML or a related field
Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the worlds leading mission capability integrator and transformative enterprise IT provider we deliver trusted highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land sea space air and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day our employees do the cant be done by solving the most daunting challenges facing our customers. Visit to learn how were keeping people around the world safe and secure.
Target Salary Range
$135000 - $216000. This represents the typical salary range for this position. Salary is determined by various factors including but not limited to the scope and responsibilities of the position the individuals experience education knowledge skills and competencies as well as geographic location and business and contract considerations. Depending on the position employees may be eligible for overtime shift differential and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer including disability and protected veterans or other characteristics protected by law.
Required Experience:
Senior IC
View more
View less