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Llm Engineer Jobs in Virginia (NOW HIRING)

The AI Security & LLM Engineer will design, secure, and optimize our next-generation generative AI infrastructure. In this role, you will bridge the gap between advanced AI capabilities and rigorous ...

The AI Security & LLM Engineer will design, secure, and optimize our next-generation generative AI infrastructure. In this role, you will bridge the gap between advanced AI capabilities and rigorous ...

The AI Security & LLM Engineer willdesign, secure, and optimize our next-generation generative AI infrastructure. In this role, you will bridge the gap between advanced AI capabilities and rigorous ...

Client is seeking a highly skilled and motivated AI/ML Engineer to join client's team and drive the development and optimization of AI solutions. * This role is ideal for someone who thrives at the ...

AI/Synthetic Engineer

Alexandria, VA · Hybrid

$110K - $135K/yr

Seven (7) or more years in ML/LLM engineering or applied data science, including production systems. * Hands-on experience with LLM application development: grounding/RAG, prompt engineering, and ...

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Llm Engineer information

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$25

$53

$76

How much do llm engineer jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for llm engineer in Virginia is $53.17, according to ZipRecruiter salary data. Most workers in this role earn between $42.88 and $61.73 per hour, depending on experience, location, and employer.

What does an LLM Engineer do?

An LLM Engineer designs, develops, and optimizes applications that leverage large language models (LLMs). They fine-tune models, integrate them into products, and improve performance through prompt engineering and model customization. This role requires expertise in machine learning, natural language processing (NLP), and software development. LLM Engineers work closely with data scientists and developers to create AI-driven solutions for various applications such as chatbots, content generation, and code assistance.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, especially those specializing in machine learning, AI, or cloud infrastructure, can earn $500,000 or more annually. These roles often require advanced skills, extensive experience, and sometimes stock options or bonuses as part of compensation packages.

What do LLM engineers do?

LLM engineers develop, optimize, and deploy large language models for various applications such as chatbots, content generation, and natural language understanding. They work with machine learning frameworks, handle data preprocessing, and fine-tune models to improve performance and accuracy.

How much do LLM engineers make?

LLM engineers typically earn between $100,000 and $180,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning and natural language processing can command higher salaries, often exceeding $200,000.

Are LLM engineers in demand?

LLM engineers are in high demand due to the rapid growth of large language models and AI applications across industries. They typically require expertise in machine learning, natural language processing, and programming skills, with many organizations actively recruiting for these roles to develop and improve AI systems.

What are the main responsibilities of an LLM Engineer on a typical project?

An LLM Engineer is typically responsible for designing, fine-tuning, and deploying large language models to solve specific business or research problems. You will collaborate closely with data scientists, product managers, and software engineers to understand requirements, select the appropriate model architectures, and integrate LLMs into production systems. Routine tasks may include data preprocessing, hyperparameter tuning, model evaluation, and monitoring model performance post-deployment. The role also often involves staying current with rapidly evolving NLP advancements to recommend and implement state-of-the-art solutions.

What are the key skills and qualifications needed to thrive in the Llm Engineer position, and why are they important?

To thrive as an LLM Engineer, you need strong expertise in machine learning, natural language processing, and proficiency with Python, along with a solid understanding of transformer-based models and deep learning frameworks like PyTorch or TensorFlow. Familiarity with cloud platforms, version control systems (e.g., Git), and tools such as Hugging Face Transformers is typically required, and certifications in AI or data science can be advantageous. Excellent problem-solving, collaboration, and communication skills help you work effectively with interdisciplinary teams and present complex findings clearly. These skills enable you to develop, fine-tune, and deploy large language models efficiently in real-world applications.

What are the most commonly searched types of Llm Engineer jobs in Virginia? The most popular types of Llm Engineer jobs in Virginia are:
What are popular job titles related to Llm Engineer jobs in Virginia? For Llm Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Llm Engineer jobs in Virginia look for? The top searched job categories for Llm Engineer jobs in Virginia are:
What cities in Virginia are hiring for Llm Engineer jobs? Cities in Virginia with the most Llm Engineer job openings:
Infographic showing various Llm Engineer job openings in Virginia as of July 2026, with employment types broken down into 3% Internship, 78% Full Time, and 19% Contract. Highlights an 64% In-person, 3% Hybrid, and 33% Remote job distribution, with an average salary of $110,595 per year, or $53.2 per hour.
AI Security & LLM Engineer

AI Security & LLM Engineer

AnaVation

Reston, VA

Full-time

Posted 3 days ago


Job description

Be Challenged and Make a Difference 
 
In a world of technology, people make the difference. We believe if we invest in great people, then great things will happen. At AnaVation, we provide unmatched value to our customers and employees through innovative solutions and an engaging culture. 

Description of Task to be Performed: 

The AI Security & LLM Engineer will design, secure, and optimize our next-generation generative AI infrastructure. In this role, you will bridge the gap between advanced AI capabilities and rigorous cybersecurity practices. You will build resilient multi-agent systems while actively defending against emerging vulnerabilities like prompt injection, data exfiltration, and model manipulation.

Core Responsibilities:  

  • System Architecture: Design and deploy robust multi-agent orchestration frameworks and Retrieval-Augmented Generation (RAG) pipelines.
  • Adversarial Defense: Develop, implement, and maintain advanced input/output guardrails to neutralize prompt injection and adversarial attacks.
  • Red Teaming: Conduct continuous LLM red teaming and simulations to identify system vulnerabilities and structural weaknesses.
  • Performance Optimization: Manage token usage, reduce latency, and engineer efficient API rate limit management strategies.
  • Secure Development: Write clean, secure, and production-grade code to integrate frontier models into enterprise applications.

Primary Languages & Technical Stack

  • Rust or Python (at least one required)
Required Qualifications:
  • Clearance: Active TS/SCI Clearance with CI Polygraph 
  • Education & Years of Experience: Bachelor’s degree and 8 years of experience related to specific functional area.  
  • Certifications: Active certifications for both IAT Level II (e.g. CompTIA Security+) and Cyber Security Service Provider (CSSP) Infrastructure Support (e.g. CompTIA Cloud+) by program onboarding date. 
  • The following individual certifications cover both certification requirements for this program: CompTIA Cybersecurity Analyst, CySA+; EC-Council Certified Network Defender (CND); GlAC Global Industrial Cyber Security Professional, GICSP; (ISC)2 System Security Certified Practitioner (SCCP). 
  • Hands-on experience and knowledge with the following: 
    • AI Architecture: Proven experience with multi-agent orchestration tools and production-grade RAG pipelines.
    • AI Security: Deep understanding of OWASP Top 10 for LLMs, prompt injection defense, and guardrail frameworks.
    • Infrastructure Management: Experience handling token optimization, context window constraints, and API throttling.
Preferred Qualifications:
  • Frontier Model Expertise: Hands-on experience deploying commercial frontier models (e.g., ChatGPT, Grok, Claude).
  • AI Developer Tools: Experience utilizing advanced AI-assisted development workflows such as Claude Code or Codex.
  • Security Testing: Background in traditional penetration testing, vulnerability assessment, or cryptographic concepts.
Benefits 
  •         Generous cost sharing for medical insurance for the employee and dependents 
  •         100% company paid dental insurance for employees and dependents 
  •         100% company paid long-term and short-term disability insurance 
  •         100% company paid vision insurance for employees and dependents 
  •         401k plan with generous match and 100% immediate vesting 
  •         Competitive Pay 
  •         Generous paid leave and holiday package 
  •         Tuition and training reimbursement 
  •         Life and AD&D Insurance
About AnaVation 
AnaVation is the leader in solving the most complex technical challenges for collection and processing in the U.S. Federal Intelligence Community. We are a US owned company headquartered in Chantilly, Virginia. We deliver groundbreaking research with advanced software and systems engineering that provides an information advantage to contribute to the mission and operational success of our customers. We offer complex challenges, a top-notch work environment, and a world-class, collaborative team.  
 
If you want to grow your career and make a difference while doing it, AnaVation is the perfect fit for you! 
 
AnaVation is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.