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Llm Engineer Remote Jobs in Washington (NOW HIRING)

Booz Allen Hamilton, Inc.

AI/ML Engineer

Chantilly, VA · On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0245425 Location: Chantilly,VA,US Share job via: Share AI/ML Engineer ... You will design and implement solutions that may include LLM-powered workflows, agent-based ...

Eliassen Group

ETL Data Engineer

Tysons, VA · Remote

$70 - $88/hr

Hybrid 3 days onsite / 2 days remote in Mclean, VA Our client seeks an ETL Data Engineer to build ... The role spans Spark-based ETL on AWS data lake platforms and development of LLM-powered agents ...

VIS IT Solutions Inc

Angular Developer

Dulles, VA · Remote

$56 - $68.50/hr

Remote - Design and build scalable, maintainable frontend systems using Angular (v16+). - Develop ... LLM-based assistants, and automation agents into frontend workflows and user experiences. - Work ...

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Llm Engineer Remote information

What is an LLM engineer?

An LLM Engineer, or Large Language Model Engineer, is a professional who designs, develops, and optimizes applications using advanced AI language models such as GPT-4 or similar technologies. Working remotely, they are responsible for integrating these models into products, fine-tuning them for specific tasks, and ensuring their performance and reliability. LLM Engineers often collaborate with data scientists, software developers, and product managers to create solutions in areas like chatbots, content generation, and natural language processing. Their work requires a strong background in machine learning, programming, and cloud computing.

What are the key skills and qualifications needed to thrive as an LLM engineer in a remote role?

To thrive as an LLM Engineer remotely, you need strong expertise in machine learning, natural language processing, and proficiency with programming languages such as Python, often supported by a degree in computer science or related fields. Familiarity with frameworks like PyTorch or TensorFlow, experience with cloud platforms (AWS, GCP), and knowledge of large language model architectures are commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication make candidates stand out. These capabilities are crucial for developing, deploying, and maintaining advanced language models while collaborating efficiently with distributed teams.

What are some typical challenges faced by remote LLM engineers when collaborating with cross-functional teams?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers to develop and deploy large language models. One common challenge is ensuring clear and consistent communication across different time zones and technical backgrounds, which can sometimes lead to misaligned project goals or delays. To overcome this, many teams rely on detailed documentation, regular virtual meetings, and collaborative project management tools. Building strong relationships remotely and proactively sharing updates can make collaboration smoother and more productive.

What is the difference between Llm Engineer Remote vs Data Scientist Remote?

AspectLlm Engineer RemoteData Scientist Remote
Required CredentialsAdvanced degree in CS, ML, or related field; experience with NLP and deep learningDegree in CS, Statistics, or related; experience with data analysis and machine learning
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesData analysis, model development, reporting; across various industries
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, tech, e-commerce, and more

While both roles involve machine learning, Llm Engineers focus on developing large language models and NLP applications, often requiring deep expertise in AI research. Data Scientists analyze data to inform business decisions, with broader industry applications. The roles share some credentials but differ in focus and daily tasks.

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

The most popular types of Llm Engineer jobs in Washington are:

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

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

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

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

What cities in Washington are hiring for Llm Engineer Remote jobs?

Cities in Washington with the most Llm Engineer Remote job openings:

Llm Engineer Remote jobs near you
Infographic showing various Llm Engineer Remote job openings in Washington as of August 2026, with employment types broken down into 88% Full Time, 2% Part Time, 2% Temporary, and 8% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

AI/ML Engineer -- Generative AI Mission Systems

Rackner

Laurel, MD • On-site, Remote

$96K - $132K/yr

Full-time

Posted 28 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.