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Spatial Ai Jobs in Virginia (NOW HIRING)

Bespoketechinc

AI Data Pipeline Engineer

Reston, VA · On-site

$119K - $143K/yr

BT-326 - AI Data Pipeline Engineer Skill Level: Senior Principal Location: Reston, VA MUST HAVE A ... Spatial * JSON (including JSON Relational Duality) * Graph #J-18808-Ljbffr

Spatial Front, Inc

Data Scientist

Arlington, VA · On-site

Spatial Front, Inc. is seeking a Data Scientist to support our growing team. The ideal candidate ... recommend AI/ML tools, frameworks, and platforms for program use. • Produce data science ...

Spatial Front, Inc

Data Scientist

Arlington, VA · On-site

Job Summary : Spatial Front, Inc. (SFI) is a recognized workplace seeking a Data Scientist to ... recommend AI/ML tools, frameworks, and platforms for program use. • Produce data science ...

IQT

Technology Architect - AI

Mclean, VA · On-site +1

Familiarity with embodied AI, including vision-language-action models, spatial reasoning, robotics, autonomous systems, reinforcement learning, and human-machine teaming. * Working knowledge of ...

IQT

Technology Architect - AI

Mclean, VA · Hybrid

Familiarity with embodied AI, including vision-language-action models, spatial reasoning, robotics, autonomous systems, reinforcement learning, and human-machine teaming. * Working knowledge of ...

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Spatial Ai information

What is Spatial AI?

Spatial AI refers to artificial intelligence systems designed to perceive, understand, and interact with the physical world in real time by processing spatial data. It combines elements of computer vision, 3D mapping, and sensor fusion to enable machines to interpret and respond to their environment, commonly used in robotics, augmented reality, and autonomous vehicles. Spatial AI technologies help machines understand objects, spaces, and movement, allowing for more advanced navigation and interaction within complex environments.

How does a spatial AI specialist typically collaborate with cross-functional teams on large-scale projects?

Spatial AI specialists often work closely with data scientists, software engineers, and domain experts to develop and deploy intelligent spatial solutions. Their role involves integrating geospatial data with machine learning models, requiring frequent communication to align on project objectives, data requirements, and deployment strategies. Collaboration is key, especially when interpreting spatial data outputs for non-technical stakeholders and adapting models based on feedback from end users. Strong teamwork skills help ensure that spatial insights are actionable and support broader organizational goals.

What are the key skills and qualifications needed to thrive as a spatial AI engineer, and why are they important?

To excel as a Spatial AI Engineer, you need a solid background in computer vision, machine learning, and spatial data analysis, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as Python, TensorFlow, OpenCV, GIS software, and experience with 3D data processing are commonly required, along with relevant certifications in AI or spatial technologies. Creative problem-solving, strong analytical thinking, and effective communication are crucial soft skills that help bridge technical solutions and real-world applications. These skills enable the development of innovative AI-driven spatial solutions that are accurate, efficient, and effectively meet organizational or client needs.

What is the difference between Spatial Ai vs GIS Analyst?

AspectSpatial AiGIS Analyst
Required CredentialsTypically requires knowledge of AI, machine learning, and spatial data processingRequires degree in geography, GIS, or related field; certifications like GISP are common
Work EnvironmentTech-focused, often in software development or data science teamsGovernment agencies, environmental firms, urban planning departments
Industry UsageEmerging in industries leveraging AI for spatial data analysisEstablished in mapping, urban planning, environmental management
Search & Comparison IntentUnderstanding AI-driven spatial analysis rolesTraditional GIS data analysis and mapping roles

Spatial Ai focuses on applying artificial intelligence to spatial data, often involving machine learning and advanced algorithms. GIS Analysts primarily work with geographic information systems to analyze and visualize spatial data. While both roles handle spatial data, Spatial Ai emphasizes AI integration, whereas GIS Analysts focus on traditional GIS tools and methods.

What jobs are available for spatial Ai?

Jobs related to spatial AI include roles such as geospatial data analyst, GIS developer, remote sensing specialist, and spatial data scientist. These positions often require skills in geographic information systems, programming, and data analysis, and may involve working with tools like ArcGIS, QGIS, or Python. Opportunities are available in industries like urban planning, environmental management, transportation, and technology companies focused on location-based services.

What are popular job titles related to Spatial Ai jobs in Virginia?

For Spatial Ai jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Spatial Ai jobs in Virginia look for?

The top searched job categories for Spatial Ai jobs in Virginia are:

What cities in Virginia are hiring for Spatial Ai jobs?

Cities in Virginia with the most Spatial Ai job openings:

Spatial Ai jobs near you
Infographic showing various Spatial Ai job openings in Virginia as of September 2026, with employment types broken down into 72% Full Time, 16% Part Time, and 12% Contract. Highlights an 89% In-person, and 11% Remote job distribution.

AI Data Pipeline Engineer

Reston, VA • On-site

Bespoketechinc
See more jobs at Bespoketechincexternal

$119K - $143K/yr

Other

Posted 24 days ago

Job description

BT-326 – AI Data Pipeline Engineer

Skill Level: Senior Principal

Location: Reston, VA

MUST HAVE A POLY CLEARANCE TO APPLY

Required Skills/Capabilities:
  • Experience working with geospatial data types (rasters and vectors)
  • Experience building data pipelines to integrate data from multiple sources:
    • Designing and implementing readers to extract metadata from data sources, with a focus on flexible readers that can adapt to new and changing data formats.
    • Designing and implementing metadata enrichment capabilities, such as data providence, pedigree, lineage, and security attributes.
    • Designing and implementing event pipelines that orchestrate data cataloging processes for different data types, including processes for data extraction, normalization, enrichment, and ingestion.
    • Leveraging AI to enhance data extract, enrichment, catalog, and discovery capabilities
  • Experience with designing and building AI agents
  • Integrating mission data with LLMs using RAG and MCP
  • Designing and building Node.js applications and dashboards connected to Oracle Databases
  • OpenAI Codex
Desired Skills/Capabilities:
  • Oracle Cloud Infrastructure (OCI)
  • Oracle AI Database 26ai
  • Oracle Exadata and/or OCI Autonomous AI Database Service on Exadata
  • AI-enabling data in Oracle Databases using Vector data type, RAG, and MCP
  • Designing multi-modal databases that integrate multiple data types, including:
    • Relational
    • Spatial
    • JSON (including JSON Relational Duality)
    • Graph
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