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Embodied 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 ...

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 ...

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Fabricator

Hampton, VA · On-site

$65K - $85K/yr

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Fabricator

Hampton, VA · On-site

$65K - $85K/yr

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Fabricator

Hampton, VA

$65K - $85K/yr

Join a team that is embodied by an unwavering commitment to professionalism, honesty, and ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Embodied Ai information

What is embodied AI?

Embodied AI refers to artificial intelligence systems that are integrated into physical entities, such as robots, which can perceive, act, and interact with the real world. Unlike traditional AI, which operates purely in digital environments, Embodied AI enables machines to understand and respond to their surroundings through sensors and actuators. This field combines elements of robotics, computer vision, natural language processing, and machine learning to create agents that can learn from their experiences and adapt to new tasks. Embodied AI is used for applications like autonomous vehicles, service robots, and interactive agents.

What are the common challenges faced by professionals working in embodied AI roles?

Professionals in Embodied AI often encounter challenges related to integrating physical hardware with complex AI algorithms. This can include troubleshooting issues between sensors, actuators, and software to ensure smooth real-world operation. Additionally, working in multidisciplinary teams—combining robotics, computer vision, and machine learning—requires strong collaboration and communication skills. Staying up-to-date with rapid advancements and testing models in unpredictable, real-world environments are also key aspects of the role.

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

To thrive as an Embodied AI Engineer, you need a strong background in robotics, computer vision, machine learning, and programming languages such as Python or C++. Familiarity with robotics middleware (like ROS), simulation tools (such as Gazebo or PyBullet), and relevant AI frameworks is typically required, along with advanced degrees in computer science or engineering often preferred. Creative problem-solving, teamwork, and effective communication are key soft skills that set candidates apart in this interdisciplinary field. These skills and qualities are essential for developing intelligent systems that can physically interact with the world and adapt to complex, real-world environments.

What is the difference between Embodied Ai vs Robotics Engineer?

AspectEmbodied AiRobotics Engineer
Required CredentialsDegree in AI, Computer Science, or related fieldsDegree in Robotics, Mechanical, or Electrical Engineering
Work EnvironmentResearch labs, AI development firms, tech companiesManufacturing plants, research labs, engineering firms
Industry UsageAI-driven applications, virtual agents, autonomous systemsPhysical robot design, automation, hardware integration
Common Search/ComparisonFocuses on AI embodiment in virtual or physical agentsFocuses on hardware and mechanical aspects of robots

Embodied Ai primarily involves developing AI systems that can operate within physical or virtual agents, emphasizing AI algorithms and interaction. Robotics Engineers focus on designing and building physical robots, integrating hardware and software. While both roles overlap in AI and robotics, Embodied Ai centers on AI behavior within agents, whereas Robotics Engineers work on the physical construction and mechanics of robots.

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

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

What cities in Virginia are hiring for Embodied Ai jobs?

Cities in Virginia with the most Embodied Ai job openings:

Infographic showing various Embodied Ai job openings in Virginia as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution.

Technology Architect - AI

Mclean, VA • Hybrid

Full-time

Re-posted 8 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