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Remote Generative Ai Engineer Jobs in Washington

Global Alliant Inc

AI Engineer

Rockville, MD · On-site +1

AI Engineer Location: Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible ... Strong experience with Python, SQL, Machine Learning, NLP, and Generative AI technologies

Global Alliant Inc

AI Engineer

Rockville, MD · Remote

$140K/yr

AI Engineer Location: Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible ... Strong experience with Python, SQL, Machine Learning, NLP, and Generative AI technologies

Node.Digital

Senior AI/ML Engineer

Herndon, VA · On-site +1

$107K - $147K/yr

Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering, model fne-tuning) * Hands-on exp with OCR, ICR and OMR technologies is a must * Good programming ...

Analytica

AI Engineer

Washington, DC · On-site +1

Analytica is seeking an AI Engineer to support the development of scalable AI applications, text ... Experience with Large Language Models (LLMs) and Generative AI technologies. * Familiarity with AI ...

Analytica

AI Engineer

Washington, DC · Remote

Analytica is seeking an AI Engineer to support the development of scalable AI applications, text ... Experience with Large Language Models (LLMs) and Generative AI technologies. * Familiarity with AI ...

Sciolex Corporation

Data & AI Engineer

Chantilly, VA · Remote

$118K - $142K/yr

Generative AI and internal business applications * Intelligent search, retrieval, and summarization ... Remote * Must be a U.S. citizen and physically located in the United States * Small, collaborative ...

Booz Allen Hamilton, Inc.

AI Engineer

Arlington, VA · On-site +1

$77K - $176K/yr

Remote Work: Yes Job Number: R0241255 Location: Arlington,VA,US Share job via: Share AI Engineer ... Experience with open-source AI projects such as Ollama or personal projects using generative AI

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Remote Generative Ai Engineer information

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What are the most commonly searched types of Generative Ai Engineer jobs in Washington?

The most popular types of Generative Ai Engineer jobs in Washington are:

What are popular job titles related to Remote Generative Ai Engineer jobs in Washington?

For Remote Generative Ai Engineer jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Engineer jobs in Washington look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Washington are:

What cities in Washington are hiring for Remote Generative Ai Engineer jobs?

Cities in Washington with the most Remote Generative Ai Engineer job openings:

Remote Generative Ai Engineer jobs near you
Infographic showing various Remote Generative Ai Engineer job openings in Washington as of August 2026, with employment types broken down into 74% Full Time, 17% Part Time, 2% Temporary, and 7% Contract. Highlights an 60% Physical, 4% Hybrid, and 36% Remote job distribution.

AI/ML Engineer -- Generative AI Mission Systems

Rackner

Laurel, MD • On-site, Remote

$96K - $132K/yr

Full-time

Re-posted 4 days ago

Job description

AI/ML Engineer — Generative AI Mission Systems

Location: Mainly remote within the United States, with onsite collaboration in Laurel, Maryland, typically one day approximately every six weeks for team-wide sprint planning.
Clearance: Active final DoD Secret clearance required

This position supports a pending contract opportunity and is contingent upon contract award, with an anticipated start in November 2026.

Build Applied AI for Secure Mission Software

Help turn generative-AI concepts into dependable capabilities used within secure mission-planning and decision-support software.

At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, prompt-engineering workflows, and inference pipelines into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical application workflows.

This role offers the opportunity to deepen your applied-AI experience, influence how emerging capabilities are designed and evaluated, and contribute to software where reliability, security, and mission usefulness matter.

This is a primarily remote role within the United States. Work will be performed using customer-provided systems, with virtual collaboration across the engineering team. Any classified work will be completed onsite at the customer location.

What You'll Do

  • Design, develop, test, and integrate AI-enabled software capabilities.
  • Build and integrate LLM-enabled capabilities into secure application workflows.
  • Develop or integrate retrieval-augmented generation capabilities.
  • Develop and support agentic-AI components and multi-step workflows.
  • Design and refine prompts, system instructions, and supporting AI workflows.
  • Build and maintain inference pipelines.
  • Connect AI capabilities with existing backend services and decision-support processes.
  • Evaluate AI outputs for grounding, reliability, accuracy, relevance, and mission usefulness.
  • Develop tests for AI-enabled functionality and support broader integration testing.
  • Demonstrate working prototypes and incorporate technical and user feedback.
  • Document AI designs, workflows, limitations, evaluation results, and implementation decisions.
  • Participate in code reviews, technical reviews, and security-remediation activities.
  • Collaborate with software engineers, security professionals, DevSecOps teams, and customer stakeholders.

What You Bring

  • A master's degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.
  • At least four years of relevant AI/ML experience that includes work with large language models, retrieval-augmented generation, and prompt engineering.
  • Hands-on experience integrating LLM-enabled software and RAG capabilities into applications or workflows.
  • Developing or supporting agentic-AI capabilities and multi-step AI workflows.
  • Designing, building, or supporting inference pipelines.
  • Ability to evaluate AI-enabled capabilities and clearly document findings, design decisions, and results.
  • Testing and documenting AI-enabled software capabilities.
  • Ability to clearly explain your personal technical ownership and contributions.
  • Strong collaboration and technical-communication skills.

Preferred Background

Experience with several of the following can strengthen your fit:

  • Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows.
  • Evaluating grounding, reliability, output quality, hallucinations, or other limitations of AI-enabled systems.
  • Integrating AI services with backend APIs or established software applications.
  • Secure software-development lifecycle and DevSecOps practices.
  • OpenShift, Kubernetes, CI/CD, or containerized application delivery.
  • Secure, restricted, disconnected, on-premises, or classified development environments.
  • Defense, government, aerospace, mission-planning, or other regulated environments.
  • Collaboration with software-engineering, cybersecurity, platform, and customer-facing technical teams.

Why Rackner

At Rackner, you will have the opportunity to build technology that supports critical defense and public-sector missions.

You will work on more than isolated AI experiments or prompt-engineering tasks. This role combines hands-on LLM integration, retrieval and agentic-AI development, secure software delivery, and close collaboration across AI, software, cybersecurity, DevSecOps, and mission-focused teams.

Rackner has delivered more than $30 million in recent federal awards and supports mission-critical work across defense, civilian, and public-sector environments. We are looking for an applied AI engineer who can build on that momentum by turning emerging generative-AI capabilities into secure, dependable software with meaningful mission impact.

Benefits & Professional Growth

  • Competitive compensation
  • Company-supported certifications aligned with current and future program work
  • 401(k) with 100% company match up to 6%
  • Medical, dental, vision, life, and disability coverage
  • Paid time off and company holidays
  • Remote-work support and home-office equipment plan
  • Fitness and wellness reimbursement
  • Weekly pay schedule
  • Professional-development and future growth opportunities

Apply

If you are an AI/ML engineer who wants to move beyond standalone prototypes and help integrate LLM, RAG, and agentic-AI capabilities into secure mission software, we would like to hear from you.