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Spatial Ai Jobs in Virginia (NOW HIRING)

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

Technology Architect - AI

Mclean, VA · On-site

$138K - $180K/yr

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

... contributing to AI-enabled, data-driven solutions. Responsibilities : • Design, analyze and develop geo-spatial solutions and product specifications for infrastructure, hydrographic and ...

... contributing to AI-enabled, data-driven solutions. Responsibilities : • Design, analyze and develop geo-spatial solutions and product specifications for infrastructure, hydrographic and ...

... contributing to AI-enabled, data-driven solutions. Responsibilities : • Design, analyze and develop geo-spatial solutions and product specifications for infrastructure, hydrographic and ...

Spatial Front, Inc. is a recognized workplace seeking a BI Team Lead to support their growing team ... AI, improving data quality and doing better data mapping • Work on executing various ETL ...

... AI-enabled, data-driven solutions for complex datasets. Responsibilities : • Design, analyze and develop geo-spatial solutions and product specifications for infrastructure, hydrographic and ...

Spatial Front, Inc. is a two-time USAToday Top Workplaces awardee and Washington Top Workplaces ... AI, improving data quality and doing better data mapping • Work on executing various ETL ...

Job Summary : Spatial Front, Inc. is seeking a Modernization SME and ART lead to support their ... AI/automation enablement, data quality improvement, DevSecOps, and help desk optimization. • ...

Spatial Surveillance Analyst - Clearance Required

Sterling, VA · On-site

$83K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Demonstrated expertise in spatial surveillance, and command and control systems with a focus on RAM ... AI-powered career tool that identifies career steps and learning opportunities Support: An internal ...

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. They are seeking an experienced AI/ML ...

Showing results 41-60

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 cities in Virginia are hiring for Spatial Ai jobs?

Cities in Virginia with the most Spatial Ai job openings:

Infographic showing various Spatial Ai job openings in Virginia as of August 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Technology Architect - AI

IQT

Mclean, VA • Hybrid

Full-time

Posted 13 days ago


Job description

$138,369 - $180,034 + bonus eligible. Offers will be commensurate with level of experience.
US-VA-McLean
Hybrid - In Office & Teleworking

This position will work closely with IQT’s government partners to understand their technology challenges and use their mastery of technology to investigate and recommend potential solutions from the venture-backed startup ecosystem, for both immediate mission needs and long term readiness. The Technology Architect team is responsible for identifying and executing investments in technology areas including (but not limited to) artificial intelligence, machine learning, enterprise search, AI automation, custom Large Language Models (LLMs), physical AI, and the security of AI systems. This position will guide the technical aspects of an investment to ensure that IQT delivers effective and compelling solutions to our Intelligence Community/Department of Defense government partners.


  • Identifies new AI/ML technology areas for investment and provides technical diligence on multiple complementary investments in that technology area.
  • Develop and negotiation of Statements of Work contracts between IQT and start-up companies.
  • Provides thought leadership in one or more areas of AI/ML subject matter expertise.
  • Leverages technical/market experience and understanding of government partner use cases to identify new topics for, and oversee development of, technical engagement strategies across short- and long-term development horizons.
  • Provide technical oversight on work programs; perform assessments of work program deliverables. Identifies and communicates paths for resolution of issues on work programs to key stakeholders and IQT Leadership.
  • Oversee development of technology architectures and solutions to address AI-related problems faced by IQT’s government partners.
  • Coordinates with customers on AI technology adoption strategy in development of multiple work programs in a government partner mission area.

Minimal Qualifications

  • Due to contractual reasons, U.S. Citizenship is required.
  • Candidates with active top-secret clearance preferred; at a minimum, candidate must meet eligibility requirements for access to classified information.
  • Advanced degree in a science or engineering discipline (or equivalent experience) preferred.
  • Minimum 5 years professional experience with some portion of that time overseeing a technology development effort in a business and/or intelligence environment.
  • Demonstrated expertise in artificial intelligence or machine learning.
  • Previous experience negotiating milestone-based Statements of Work contracts.

Preferred Qualifications

  • Demonstrated expertise in applied AI/ML, generative and multimodal AI, enterprise search, agentic systems, workflow automation, NLP, or production AI engineering: 
    • Experience designing, evaluating, deploying, or securing LLMs, multimodal models, RAG systems, AI agents, or human-AI decision-support tools. 
    • Knowledge of AI-enabled threat intelligence and cyber defense, including detection, vulnerability prioritization, incident investigation, and response. 
    • Understanding of AI security across data, models, prompts, retrieval, memory, tools, APIs, infrastructure, and third-party components. 
    • Familiarity with AI threats such as prompt injection, jailbreaks, unsafe tool use, data or model poisoning, evasion, model extraction, and sensitive-data leakage. 
    • Knowledge of agent security, including identity, authorization, least privilege, sandboxing, containment, MCP security, and supply-chain integrity. 
    • Experience with AI evaluation, assurance, and red teaming, including threat modeling, adversarial testing, safety evaluations, monitoring, and incident response. 
    • Knowledge of AI-enabled security operations, including threat hunting, vulnerability analysis, malware analysis, digital forensics, alert triage, and detection engineering. 
    • Familiarity with privacy-preserving AI, including federated learning, differential privacy, secure aggregation, confidential computing, and multiparty computation. 
    • Understanding of explainable and auditable AI, including interpretability, uncertainty, evidence traceability, and decision provenance. 
    • Experience using generative AI, world models, digital twins, or multi-agent simulations for red teaming, mission rehearsal, synthetic data, and defensive testing. 
    • Familiarity with embodied AI, including vision-language-action models, spatial reasoning, robotics, autonomous systems, reinforcement learning, and human-machine teaming. 
    • Working knowledge of modern AI architectures, including Transformers, mixture-of-experts, diffusion, state-space, retrieval, multimodal, agentic, and edge AI systems. 
    • Understanding of the AI lifecycle, including data preparation, training, adaptation, evaluation, deployment, monitoring, governance, and retirement. 
    • Experience with MLOps, LLMOps, or AgentOps practices and supporting production infrastructure. 
    • Hands-on experience with Python, JavaScript/TypeScript, Go, or Rust and with cloud, GPU, API, container, or production data environments. 
    • Ability to assess emerging AI technologies, separate demonstrated performance from marketing claims, and evaluate mission value, limitations, risks, and adoption barriers. 
  • Commitment to continued understanding of new AI technologies and their strategic advantages. 
  • Capable of analyzing complex problems including identifying root cause issues, generating a concise summary of analysis; and presenting recommendations for non-technical audiences. 
  • Startup or entrepreneurial experience and proven ability to thrive in a non-traditional, entrepreneurial environment. 
  • Comfortable presenting complex technology subjects to both technical and non-technical audiences. 
  • Prior experience working with the U.S. Intelligence Community. 
  • Strong writer: experience in both technical writing and proposal/contract writing is preferred. 

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. 

PM22